Semi-automatic dimensioning with imager on a portable device

Information

  • Patent Grant
  • 10140724
  • Patent Number
    10,140,724
  • Date Filed
    Friday, December 5, 2014
    9 years ago
  • Date Issued
    Tuesday, November 27, 2018
    5 years ago
Abstract
A method of operating a dimensioning system to determine dimensional information for objects is disclosed. A number of images are acquired. Objects in at least one of the acquired images are computationally identified. One object represented in the at least one of the acquired images is computationally initially selected as a candidate for processing. An indication of the initially selected object is provided to a user. At least one user input indicative of an object selected for processing is received. Dimensional data for the object indicated by the received user input is computationally determined.
Description
BACKGROUND

Technical Field


This disclosure generally relates to the field of automated package handling.


Description of the Related Art


Package handling efficiency is increased by automating aspects of the process. Two processes that are time consuming are the determination of the package dimensions and/or determining dimensional weight. Package dimensions are important to optimize the loading process. In addition, knowing the remaining space is also useful.


The concept of dimensional weight has commonly been adopted by the transportation industry in most parts of the world as a standard way of determining charges for the shipment of packaged goods. Determining the dimensional weight of an object involves measuring the cubic space occupied by the object, or dimensioning. Dimensional weight is widely used because shipping costs calculated based on weight of the goods alone would render it unprofitable for carriers when the shipped goods have low density, e.g., small weight but occupy a large space. By using dimensional weight in calculating shipping costs, on the other hand, carriers can charge based on either the actual weight or the dimensional weight of the shipped goods, usually depending on whichever is greater. Moreover, by dimensioning objects, such as parcels, packages, and pallets, carriers, warehouses, shipping retailers, postal companies, or the like may optimally utilize their storage space and charge for the service accordingly.


Dimensional weight involves the volumetric weight of an object, and, more specifically, the cubic space the object occupies. Typically, the dimensional weight of an object is calculated as the multiplicative product of the object's length, width, and height divided by a constant. For example, in the United States, the dimensional weight of an object is calculated by domestic air carriers as (length×width×height)/166, with all dimensions in inches. A parcel weighing 25 pounds and having volumetric dimensions of 20×15×15 inches would have, using the above formula, a dimensional weight of 27.1 pounds. In this example, the shipping charge would be determined based on the dimensional weight of 27.1 pounds, because it is greater than the actual weight of 25 pounds.


To expedite the dimensioning process and to facilitate accurate dimensioning, companies have invested in various automatic dimensioning systems. One type of dimensioning system, such as a volume dimensioning application, performs volumetric dimensioning of objects by first capturing an image of the objects and then finding those objects in the image. For instance, an image capturing device may be utilized to capture an image of a number of parcels waiting to be dimensioned. Afterwards, a computing device may select one of the parcels from the parcels in the image to calculate the dimensional weight for. To do so, the computing device may need to estimate the boundary of the selected parcel to determine its approximate length, width, and height for the calculation. However, it can be very difficult at times to discern a particular object or objects in an image due to insufficient lighting or the presence of numerous objects in the same image. Although such a volume dimensioning application may be designed as a standalone, automatic application, issues such as those mentioned above may cause inaccuracy in the dimensioning process and ultimately result in delay and extra operational costs.


BRIEF SUMMARY

A method of operating a dimensioning system to determine dimensional information for objects may be summarized as including acquiring a number of images; computationally identifying objects in at least one of the acquired images; computationally initially selecting one object represented in the at least one of the acquired images as a candidate for processing; providing an indication to a user indicative of the initially selected object; receiving at least one user input indicative of an object selected for processing; and computationally determining dimensional data for the object indicated by the received user input.


Receiving at least one user input indicative of an object selected for processing may include receiving a user selection that confirms the initially selected one object as the object for processing. Computationally determining dimensional data for the object indicated by the received user input may include determining a dimensional weight based on an estimated perimeter of the initially selected one object as represented in the acquired image. Receiving at least one user input indicative of an object selected for processing may include receiving a user selection that indicates an object other than the initially selected one object as the object for processing. Computationally determining dimensional data for the object indicated by the received user input may include determining a dimensional weight based on an estimated perimeter of the object indicated by the received user selection as the object is represented in the acquired image. The method may further include providing an indication to the user indicative of a currently selected object, the indication visually distinguishing the currently selected object in a display of the acquired image from any other object represented in the display of the acquired image. Receiving at least one user input indicative of an object selected for processing may include receiving a user selection that indicates at least a portion of a new perimeter for the object for processing. Computationally determining dimensional data for the object indicated by the received user input may include computationally determining dimensional data based on the new perimeter of the object represented in the acquired image. Providing an indication to a user indicative of the initially selected object may include displaying the acquired image and visually distinguishing the initially selected object in the display of the acquired image from any other objects represented in the display of the acquired image. Visually distinguishing the initially selected object in the display of the acquired image from any other objects represented in the display of the acquired image may include displaying a border about at least a portion of the initially selected object in the display of the acquired image. Receiving at least one user input indicative of an object selected for processing may include receiving at least one signal representing a position in the image that indicates a position of at least a portion of a new perimeter for the object for processing. Visually distinguishing the initially selected object in the display of the acquired image from any other objects represented in the display of the acquired image may include displaying a draggable border about at least a portion of the initially selected object in the display of the acquired image. Receiving at least one user input indicative of an object selected for processing may include receiving at least one signal representing a dragging of the draggable border to a new position that indicates at least a portion of a new perimeter for the object for processing. Computationally determining dimensional data for the object indicated by the received user input may include computationally determining a dimension of at least one of a box, a package, a parcel, a pallet or a document represented in the acquired image.


A method of operating a dimensioning system to determine dimensional information for objects may be summarized as including acquiring a number of images; computationally identifying objects or spaces in at least one of the acquired images; determining dimensional data for at least one object or space; and receiving at least one user input indicative of an object or space selected for processing.


The method may further include computationally determining dimensional data for the object or space selected by the received user input. The method may further include computationally revising the determined dimensional data for the at least one object or space in response to the received user input. Receiving at least one user input may include receiving at least one user input in the form of at least one of a keyboard entry, a computer mouse entry, a touch-screen device entry, a voice command, an audible command, and a bar code reading. Receiving at least one user input indicative of an object or space selected for processing may include receiving a user selection that confirms the initially selected one object or space as the object for processing. Computationally determining dimensional data for the object or space selected by the received user input may include determining a dimensional weight based on an estimated perimeter of the initially selected one object as represented in the acquired image. Computationally determining dimensional data for the object or space selected by the received user input may include determining a dimensional data based on an estimated perimeter of the initially selected one space as represented in the acquired image. Receiving at least one user input indicative of an object or space selected for processing may include receiving a user selection that indicates an object or space other than the initially selected one object or space as the object or space for processing. Computationally determining dimensional data for the object or space selected by the received user input may include determining a dimensional weight based on an estimated perimeter of the object selected by the received user selection as the object is represented in the acquired image. Computationally determining dimensional data for the object or space selected by the received user input may include determining a dimensional data based on an estimated perimeter of the space selected by the received user selection as the space is represented in the acquired image. The method may further include providing an indication to the user indicative of a currently selected object or space, the indication visually distinguishing the currently selected object or space in a display of the acquired image from any other object or space represented in the display of the acquired image. Receiving at least one user input indicative of an object or space selected for processing may include receiving a user selection that indicates at least a portion of a new perimeter for the object or space for processing. Computationally determining dimensional data for the object or space selected by the received user input may include computationally determining dimensional data based on the new perimeter of the object or space represented in the acquired image in response to the received user input.


A dimensioning system to determine dimensional information for objects may be summarized as including an imager configured to acquire images; a user input/output system configured to display images and to receive user input; and a processor configured to identify objects in the acquired images, initially select one of the identified objects for processing, cause the acquired images to be displayed via the user input/output system along with an indication indicative of the initially selected one object, and computationally determine dimensional data for an object indicated by at least one user input received via the user input/output system.


The processor may be configured to determine a dimensional weight based on an estimated perimeter of the initially selected one object as represented in the acquired image in response to at least one user input confirming the initially selected one object as the object to be processed. The processor may be configured to computationally determine a dimensional weight based on a new perimeter of the initially selected one object represented in the acquired image in response to at least one user input indicative of the new perimeter. The processor may be configured to determine a dimensional weight based on an estimated perimeter of an object represented in the acquired image other than the initially selected one object in response to at least one user input selecting the other object as the object to be processed. The processor may be configured to determine a dimensional weight based on a user identified perimeter of an object represented in the acquired image other than the initially selected one object in response to at least one user input selecting the other object as the object to be processed and identifying at least a portion of the user identified perimeter. The processor may be configured to cause acquired images to be displayed via the user input/output system along with an indication indicative of the initially selected one object by displaying a draggable border about at least a portion of the initially selected object in the display of the acquired image. The processor may be further configured to cause acquired images to be displayed via the user input/output system along with an indication indicative of a user selected object by displaying a draggable border about at least a portion of a user selected object in the display of the acquired image. The user input/output system may include a touch-sensitive display. The processor may be further configured to cause the user input/output system to display dimensional data for one or more objects in the acquired images.


A dimensioning system to determine dimensional information for confined empty spaces may be summarized as including an imager to acquire images; a user input/output system to display images and to receive user input; and a processor configured to identify spaces in the acquired images, initially select one of the identified spaces for processing, cause the acquired images to be displayed via the user input/output system along with an indication indicative of selection of the initially selected space, and computationally determine dimensional data for a space indicated by at least one user input received via the user input/output system.


The processor may be configured to computationally determine the dimension data based on an estimated perimeter of the initially selected space as represented in the acquired image in response to at least one user input confirming the initially selected space as the space to be processed. The processor may be configured to computationally determine the dimensional data based on a new perimeter of the initially selected space represented in the acquired image in response to at least one user input indicative of the new perimeter. The processor may be configured to computationally determine the dimensional data based on an estimated perimeter of a space represented in the acquired image other than the initially selected space in response to at least one user input selecting the other space as the space to be processed. The processor may be configured to computationally determine the dimensional data based on a user identified perimeter of a space represented in the acquired image other than the initially selected space in response to at least one user input selecting the other space as the space to be processed and identifying at least a portion of the user identified perimeter. The processor may be configured to cause acquired images to be displayed via the user input/output system along with an indication indicative of the initially selected space by displaying a draggable border about at least a portion of the initially selected space in the display of the acquired image. The processor may be further configured to cause acquired images to be displayed via the user input/output system along with an indication indicative of a user selected space by displaying a draggable border about at least a portion of a user selected space in the display of the acquired image. The user input/output system may include a touch-sensitive display. The processor may be further configured to cause the user input/output system to display dimensional data related to one or more objects.


A computer-readable medium storing therein instructions to cause a computer to execute a process related to determining dimensional information for objects may be summarized as including displaying an image; identifying objects represented in the displayed image; initially selecting one object of the objects represented in the displayed image for processing; causing the displayed image and an indication indicative of the initially selected one object to be displayed; receiving user input; and determining dimensional data for an object indicated by at least one user input.


Determining dimensional data for an object indicated by at least one user input may include determining a dimensional weight based on an estimated perimeter of the initially selected one object as represented in the displayed image in response to at least one user input confirming the initially selected one object as the object to be processed. Determining dimensional data for an object indicated by at least one user input may include determining a dimensional weight based on a new perimeter of the initially selected one object represented in the displayed image in response to at least one user input indicative of the new perimeter. Determining dimensional data for an object indicated by at least one user input may include determining a dimensional weight based on an estimated perimeter of an object represented in the displayed image other than the initially selected one object in response to at least one user input selecting the other object as the object to be processed. Determining dimensional data for an object indicated by the at least one user input may include determining a dimensional weight based on a user identified perimeter of an object represented in the displayed image other than the initially selected one object in response to at least one user input selecting the other object as the object to be processed and identifying at least a portion of the user identified perimeter. Causing the displayed image and an indication indicative of the initially selected one object to be displayed may include causing the displayed image to be displayed and causing a draggable border about at least a portion of the initially selected one object to be displayed in the displayed image. Causing the displayed image and an indication indicative of the initially selected one object to be displayed may include causing the displayed image to be displayed and causing a draggable border about at least a portion of a user selected object to be displayed in the displayed image.


A computer-readable medium storing therein instructions to cause a computing system to execute a process related to determining dimensional information for objects may be summarized as including displaying an image; identifying objects or spaces represented in the displayed image; providing an indication to a user; receiving user input; and determining dimensional data for an object or space in response to the user input.


Providing an indication to a user may include indicating a problem related to an object or space of the objects or spaces in the displayed image to the user. Indicating a problem related to an object or space of the objects or spaces in the displayed image to the user may include indicating a problem in determining dimensional data for an object or space of the objects or spaces in the displayed image to the user. Receiving user input may include receiving the user input in the form of at least one of a keyboard entry, a computer mouse entry, a touch-screen device entry, a voice command, an audible command, and a bar code reading. The process may further include displaying a second image after receiving the user input; identifying objects or spaces represented in the second image; and receiving a second user input. Determining dimensional data for an object or space in response to the user input may include determining dimensional data for an object or space identified in the second image in response to the second user input. The process may further include determining dimensional data for one of the identified objects or spaces in the displayed image prior to receiving the user input. The process may further include displaying a dimensional data for an object or space.


A processor-implemented method of selecting an object from at least one object in an image to process information about the selected object may be summarized as including providing an image of the at least one object; selecting a first object of the at least one object in the image; updating the image to indicate the selection of the first object; receiving an input related to the selection of the first object; updating the image to indicate the input; and computationally determining dimensional data related to one of the at least one object using the input.


Updating the image to indicate the selection of the first object may include updating the image to indicate an estimated perimeter around the first object. Receiving an input related to the selection of the first object may include receiving the input selecting a second object of the at least one object that is different than the first object. Receiving an input related to the selection of the first object may include receiving the input to modify an aspect related to the indication of the selection of the first object. Receiving the input to modify an aspect related to the indication of the selection of the first object may include receiving the input to modify an estimated perimeter of the first object. Receiving an input related to the selection of the first object may include receiving the input as a user selection on a portion of a touch-screen device to select a second object of the at least one object. Receiving an input related to the selection of the first object may include receiving the input as a boundary drawn on a touch-screen device around an image of a second object of the at least one object to select the second object. Receiving an input related to the selection of the first object may include detecting a number of contacts at a number of positions on a touch-screen device, the contacts indicative of a number of corners of the first object. Receiving an input related to the selection of the first object may include receiving at least one user input indicative of a new position of a corner of the first object in the image displayed on a touch-screen device. Receiving an input related to the selection of the first object may include receiving at least one user input indicative of a perimeter of one of the at least one object on a touch-screen device indicative of a selection of the one of the at least one object. Determining dimensional data related to one of the at least one object using the input may include determining a dimensional weight of the one of the at least one object based on a computationally determined estimated perimeter of the one of the at least one object. Determining dimensional data related to one of the at least one object using the input may include determining a dimensional weight of the one of the at least one object based on a user identified perimeter of the one of the at least one object.


A processor-implemented method of selecting an object from at least one object in an image to process information about the selected object may be summarized as including displaying the image of the at least one object; selecting a first object of the at least one object in the image; updating the image to indicate the selection of the first object; receiving an input related to the selection of the first object; and updating the image to indicate the input.


Updating the image to indicate the selection of the first object may include updating the image to indicate an estimated perimeter around the first object. Receiving an input related to the selection of the first object may include receiving the input selecting a second object of the at least one object that is different than the first object. Receiving an input related to the selection of the first object may include receiving the input to modify an aspect related to the indication of the selection of the first object. Receiving the input to modify an aspect related to the indication of the selection of the first object may include receiving the input to modify an estimated perimeter of the first object. Receiving an input related to the selection of the first object may include receiving the input as a user selection on a portion of a touch-screen device to select a second object of the at least one object. Receiving an input related to the selection of the first object may include receiving the input as a boundary drawn on a touch-screen device around an image of a second object of the at least one object to select the second object. Receiving an input related to the selection of the first object may include detecting a number of contacts at a number of positions on a touch-screen device, the contacts indicative of a number of corners of the first object. Receiving an input related to the selection of the first object may include receiving at least one user input indicative of a new position of a corner of the first object in the image displayed on a touch-screen device. Receiving an input related to the selection of the first object may include receiving at least one user input indicative of a perimeter of one of the at least one object on a touch-screen device indicative of a selection of the one of the at least one object. Receiving an input may include receiving an audible command from a user. Receiving an input may include receiving a verbal command from a user. The method of claim may further include computationally determining dimensional data related to one of the at least one object using the input. Determining dimensional data related to one of the at least one object using the input may include determining a dimensional weight of the one of the at least one object based on a computationally determined estimated perimeter of the one of the at least one object. Determining dimensional data related to one of the at least one object using the input may include determining a dimensional weight of the one of the at least one object based on a user identified perimeter of the one of the at least one object.





BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS


FIG. 1A is a block diagram showing a dimensioning system configured to determine dimensional information related to objects according to one non-limiting illustrated embodiment.



FIG. 1B is a block diagram showing another dimensioning system configured to determine dimensional information related to objects according to one non-limiting illustrated embodiment.



FIG. 1C is a block diagram showing yet another dimensioning system configured to determine dimensional information related to objects according to one non-limiting illustrated embodiment.



FIG. 2A is a block diagram showing an electronic device according to one non-limiting illustrated embodiment.



FIG. 2B is a block diagram showing another electronic device according to one non-limiting illustrated embodiment.



FIG. 3A is a flow chart showing a process of operating a dimensioning system to determine dimensional information for objects according to one non-limiting illustrated embodiment.



FIG. 3B is a flow chart showing a process of operating a dimensioning system to determine dimensional information for objects according to another non-limiting illustrated embodiment.



FIG. 4A is a flow chart showing a processor-implemented method of selecting an object from at least one object in an image to process information about the selected object according to one non-limiting illustrated embodiment.



FIG. 4B is a flow chart showing a processor-implemented method of selecting an object from at least one object in an image to process information about the selected object according to another non-limiting illustrated embodiment.



FIG. 5A is a flow chart showing a process performed by a program stored in a computer-readable medium according to one non-limiting illustrated embodiment.



FIG. 5B is a flow chart showing a process performed by a program stored in a computer-readable medium according to another non-limiting illustrated embodiment.



FIG. 6A is a diagram of an image of two objects according to one non-limiting illustrated embodiment.



FIG. 6B is a diagram of the image of the two objects of FIG. 6A and an indication of the selection of one of the two objects according to one non-limiting illustrated embodiment.



FIG. 6C is a diagram of the image of the two objects of FIG. 6A, an indication of the selection of one of the two objects, and an indication of a user selection of the other of the two objects according to one non-limiting illustrated embodiment.



FIG. 6D is a diagram of the image of the two objects of FIG. 6A, an indication of the selection of one of the two objects, and an indication of a user selection of the other of the two objects according to another non-limiting illustrated embodiment.



FIG. 6E is a diagram of an image of two objects and an indication of an estimated boundary of one of the two objects according to one non-limiting illustrated embodiment.



FIG. 6F is a diagram of the image of the two objects of FIG. 6E and an indication of a user modification of the estimated boundary of one of the two objects according to one non-limiting illustrated embodiment.





In the drawings, identical reference numbers identify similar elements or acts. The sizes and relative positions of elements in the drawings are not necessarily drawn to scale. For example, the shapes of various elements and angles are not drawn to scale, and some of these elements are arbitrarily enlarged and positioned to improve drawing legibility. Further, the particular shapes of the elements as drawn, are not intended to convey any information regarding the actual shape of the particular elements, and have been solely selected for ease of recognition in the drawings.


DETAILED DESCRIPTION

In the following description, certain specific details are set forth in order to provide a thorough understanding of various disclosed embodiments. However, one skilled in the relevant art will recognize that embodiments may be practiced without one or more of these specific details, or with other methods, components, materials, etc. In other instances, well-known structures associated with computing systems, imagers (e.g., cameras), and/or transport mechanisms (e.g., conveyors) have not been shown or described in detail to avoid unnecessarily obscuring descriptions of the embodiments.


Unless the context requires otherwise, throughout the specification and claims which follow, the word “comprise” and variations thereof, such as, “comprises” and “comprising” are to be construed in an open, inclusive sense that is as “including, but not limited to.”


Reference throughout this specification to “one embodiment” or “an embodiment” means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.


The headings and Abstract of the Disclosure provided herein are for convenience only and do not interpret the scope or meaning of the embodiments.



FIG. 1A shows a dimensioning system 10a configured to determine dimensional information related to objects according to one non-limiting illustrated embodiment. In one embodiment, the dimensioning system 10a includes a computing system 12 communicatively coupled with a user input device 14, a user output device 16, and a data storage device. In various embodiments, an imager 15 may be communicatively coupled to the data storage device 18, the computing system 12, or both. In one embodiment, the dimensioning system 10a may comprise a collection of individual standalone devices. In another embodiment, the dimensioning system 10a may comprise an integrated device plus at least one standalone device coupled to the integrated device, such as a handheld computer system by INTERMEC TECHNOLOGIES™ coupled to a standalone imager. For example, as shown in FIG. 1B, a computing system 12, a user input device 14, a user output device 16, and a data storage device 18 may be integral components of a dimensioning system 10b, with an external imager 15 coupled to either or both of the computing system 12 and the data storage device 18. In an alternative embodiment, a dimensioning system 10 may comprise one integrated device, such as a personal digital assistant (PDA) or one of the imaging-capable handheld computer systems by INTERMEC TECHNOLOGIES™. For example, as shown in FIG. 1C, a dimensioning system 10c may be an integrated device having a computing system 12, a user input device 14, a user output device 16, a data storage device 18, and an imager 15 as its integral components.


In some embodiments, the computing system 12 may be, for example, a desktop computer, a notebook computer, a handheld computer, a PDA, a workstation, a mainframe computer, or a processor in any type of the aforementioned computers or devices. The user input device 14 may be, for example, a keyboard, a computer mouse, a touch-screen device, a voice recognition device, a bar code reader, or any combination thereof. The user output device 16 may be, for example, a standalone monitor (e.g., a liquid-crystal display monitor or a cathode-ray tube monitor), a display screen, an auditory device, or a touch-screen device. In one embodiment, the user input device 14 and the user output device 16 may each be a part of a touch-screen device, which, as known in the art, is a display device that can detect the presence and location of a touch within a display area of the display device. For example, a touch-screen device including both the user input device 14 and the user output device 16 may have a screen that is operable to display an image and detect a contact to the screen by a user's finger, hand, or a writing tool such as a stylus. The data storage device 18 is preferably operable to store digital data that includes textual and numerical data, digitized images, and data input by a user of the dimensioning system 10, etc. The data storage device 18 may comprise a memory device such as, for example, a hard drive (whether as an integral part of the dimensioning system 10 or as a standalone device), a recording medium, or an integrated-circuit memory device (e.g., memory chip). The imager 15 may be, for example, a charge-coupled device (CCD), a complementary metal-oxide-semiconductor (CMOS) active-pixel sensor, or any similar image sensing or capture device that converts an optical image to a signal representative of the image.


In operation, the dimensioning system 10 of FIGS. 1A-1C is preferably operable to acquire or capture an image of one or more objects and/or spaces using the imager 15 as image data. The one or more objects may be, for instance, parcels, packages, pallets, documents, boxes, or the like that need to have their respective dimensional weight or dimensions determined. The image data representing the captured image of the one or more objects and/or spaces may be stored in the data storage device 18. The captured image may also be displayed by the user output device 16 as directed by the computing system 12. The computing system 12 may, without any external input, automatically select one of the objects or spaces represented in the image as the object or space on which further data processing will be performed, e.g., to determine the dimensional weight of the selected object or a dimension related to the selected space. An indication of the selection of the object or space may be reflected in the displayed image. For example, the representation of the selected object or space may be highlighted, circled, flashed, marqueed, represented in a different color, or somehow marked to visually indicate to a viewer (e.g., user) of such selection by the computing system 12. As a result, the image of the one or more objects and/or spaces and the indication of the selection of one of the objects or spaces by the computing system 12 are displayed on the user output device 16 for user interaction before further computation by the computing system 12 is carried out. In an alternative embodiment, the computing system 12 makes no selection and simply causes the user output device 16 to display the image of the objects and/or spaces and awaits the user to make a user input selecting or identifying one of the objects or spaces before the computing system 12 performs computation based on the user input. In another alternative embodiment, the computing system 12 displays information about the object such as dimensions, color, data from a bar code symbol, or information indicating previously chosen objects.


A user of the dimensioning system 10 viewing the displayed image of the one or more objects may provide user input through the user input device 14. If the user agrees that it is the selected object on which further computation is to be performed, the user input may simply be one form of validation, such as, for example, a click of a computer mouse, a touch on a “Yes” button or user selectable icon on the user input device 14 in the form of a touch-screen device, pressing and releasing of a key on a keyboard, a check mark entered in an input field displayed on the user input device 14 in the form of a touch-screen device, or an audible or verbal command such as “Object 3,” for example. If the user agrees with the selection but wishes to make some modification to the selection (e.g., to correct the estimated perimeter of the selected object before dimensional weight is calculated based on the estimated perimeter), the user input may include both a validation and a modification, or simply a modification. For example, the perimeter estimated by the computing system 12 may be entirely or partially incorrect due to insufficient lighting in the image or too many or overlapping objects in the image making it difficult to discern the perimeter of the selected object. In such case, the user may modify all or a portion of the perimeter of the selected object as estimated by the computing system 12 and show in the image on the output device 16. If, however, the user disagrees with the selection by the computing system 12 and wishes to select a different object among the objects represented in the displayed image, the user input may include a selection of a different object in the image. For instance, when an object A of two objects represented in the displayed image is selected by the computing system 12 and the user wishes to select an object B instead, the user may enter his/her selection of object B by one of various ways. In another situation, there may be an inadequate image for certain packages, such as when a package is viewed straight on, only two of the tree dimensions are visible. Accordingly, in one embodiment, the computing system 12 may request that the user perform a task, such as issuing the command “Please move right or left and re-image Object 3,” for example.


The method by which the user enters his/her input may include, but is not limited to, one of the following: selecting or indicating at least a portion of the representation of object B in the displayed image; drawing or otherwise indicating a boundary around the representation of object B in the displayed image displayed on a touch-screen device; drawing a mark on or otherwise marking object B in the displayed image; and/or pointing out or otherwise indicating or selecting the corners or other specific features of object B in the displayed image. The user may take such action by, for example, manipulating a cursor or pointer icon displayed in the image using a pointer device (e.g., computer mouse, trackball, joystick, and rocker switch or arrow keys), or by using audible or verbal commands. The user may take such action by touching one or more portions of a touch sensitive screen on which the image is displayed, for example, to select portions of the objects B or user selectable icons.


Whether the user input validates or modifies the selection of the computing system 12, or selects a new object in the image, the user output device 16 may display the user input along with the representation of the at least one object in the image. For example, the user may validate the selection of a first object of the objects represented in the image yet at the same time modify the estimated perimeter of the representation of the first object by tracing or otherwise indicating the actual perimeter (i.e., indicated perimeter) of the representation of the first object on the display of the user output device 16. For instance, the user may select a portion of the perimeter of object and drag the selected portion using a pointer device (e.g., mouse, trackball, joystick, etc), a finger or a stylus (e.g., touch screen). In such case, the user output device 16 may show the traced line on the display as drawn by the user. If the user selects a second object of the objects represented in the image (e.g., by drawing a cross or a check mark on the second object), the user output device 16 may then represent the cross or check mark on the display. This provides an interaction between the dimensioning system 10 and the user in that the user provides user input as a part of the overall process of determining a dimensional value of the selected object (e.g., volume dimensioning), and the dimensioning system 10 provides an indication or feedback to the user of the user's input and performs computation based on the user input.


After the user provides input to the dimensioning system 10 through the user input device 14, the computing system 12 performs computation related to the selected object based on the user input. In the case of volume dimensioning where the dimensional weight of an object is computed, the computing system 12 computes the dimensional weight of the selected object based on an estimated or indicated perimeter of the selected object. More specifically, in one embodiment, the computing system 12 is able to estimate a length, width, and height of the selected object, for example, by using the estimated or indicated perimeter of the selected object. Once the dimensional weight of the selected object has been determined, the charge for shipment of the selected object may then be determined.


Thus, by allowing the user to validate the object selection by the computing system 12, or by allowing the user to select an object for the computing system 20 to perform volume dimensioning on, or both, issues related to inaccuracy caused by selection of a wrong object or an erroneous estimation of the object's perimeter (and thus dimensions) by the computing system 12 due to insufficient lighting or presence of numerous objects in the image or other issues may be avoided. The user interaction serves as a check in the dimensioning process, ensuring that the correct object is selected and that computation is based on dimensions derived from a correct perimeter of the selected object.



FIG. 2A shows an electronic device 20a according to one non-limiting illustrated embodiment. The electronic device 20a may be coupled to an imager 25 operable to acquire or otherwise capture images and provide image data representing the acquired or captured images to the electronic device 20a. In one embodiment, the electronic device 20a may include a processing component 22, a user input component 24, and a display component 26. The display component 26 may display an image provided by the imager 25, and such image may include one or more objects for which a dimensional value (e.g., a dimensional weight) is to be determined. The user input component 24 may receive input from a user of the electronic device 20a. In one embodiment, the display component 26 may be a liquid-crystal display, and the user input component 24 may be a keyboard having a plurality of keys for the user to enter input. In an alternative embodiment, the electronic device 20a may include a touch-screen display that serves as both the user input component 24 (e.g., touch-sensitive overlay) and the display component 26 (e.g., LCD, O-LCD). In another embodiment, the electronic device 20a may include a touch-screen display that serves as both the user input component 24 and the display component 26, while the electronic device 20a further includes a keyboard having a plurality of keys as another portion of the user input component 24. For example, the user may enter input via either the touch-screen display, the keyboard, or both. The processing component 22 is coupled to the user input component 24 and the display component 26.


In one embodiment, the processing component 22 is operable to determine from an image captured by the imager 25 an approximate perimeter of a first object of at least one object in the image. The processing component 22 may cause the display component 26 to display the captured image and an indicator that indicates the approximate perimeter of the first object. Upon receiving at least one input from the user via the user input component 24, the processing component 22 determines a dimensional value of one of the objects in the displayed image based on the user input. For example, the processing component 22 may perform computation for volume dimensioning on the first object if the user input validates or modifies the approximate perimeter of the first object. If the user input modifies the approximate perimeter of the first object, the computation will be based on the modified perimeter. Otherwise, in the case of the user input indicates validation, the computation will be based on the approximate perimeter determined by the processing component 22. Alternatively, if the user selects a second object different than the first object from objects represented in the displayed image, the processing component 22 may perform volume dimensioning on the second object to determine the dimensional weight of the second object.



FIG. 2B shows a diagram of an electronic device 20b according to another non-limiting illustrated embodiment. The electronic device 20b may include a processing component 22, a user input component 24, a display component 26, and an imager 25. In one embodiment, the electronic device 20b may perform functions similar to those performed by the electronic device 20a of FIG. 2A. Therefore, in the interest of brevity, a description of the components of the electronic device 20b will not be repeated.



FIG. 3A shows a flow chart of a process 30a of operating a dimensioning system to determine dimensional information for objects according to one non-limiting illustrated embodiment. In one embodiment, at 31a, a number of images is captured or acquired. At 32a, objects in at least one of the acquired images are computationally identified, for example, by a processor-based system or a computing system. At 33a, one object represented in the at least one of the acquired images is computationally initially selected as a candidate for processing. In one embodiment, the selection is made automatically by a computing system or a processor-based system without any human interaction. An indication to a user to indicate the initially selected object is provided at 34a. At least one user input indicative of an object selected for processing is received at 35a. Then, at 36a, dimensional data for the object indicated by the received user input is computationally determined. For example, in one embodiment, a dimension of at least one of a box, a package, a parcel, a pallet or a document represented in the acquired image is computationally determined.


In one embodiment, the at least one user input received may include a user selection that confirms the initially selected one object as the object for processing. In another embodiment, the at least one user input received may include a user selection that indicates an object other than the initially selected one object as the object for processing. For example, when the user desires to determine dimensional data for an object that is different than the object initially selected by an automatic process executed in a computing system, the user manually selects the user-selected object before the computing system proceeds further. When the user input confirms the initially selected one object as the object for processing, in one embodiment, a dimensional weight of the initially selected one object is determined based on an estimated perimeter of the initially selected one object as represented in the acquired image. Alternatively, when the user input selects a different object, a dimensional weight of the user-selected object is determined based on an estimated perimeter of the user-selected object as represented in the acquired image. Further, when the user input selects a different object, process 30a may additionally include (not shown) providing an indication to the user indicative of a currently selected object to visually distinguish the currently selected object in a display of the acquired image from any other object represented in the display of the acquired image.


In one embodiment, the at least one user input received indicates at least a portion of a new perimeter for the object for processing. In such case, in one embodiment, the dimensional data is computationally determined based on the new perimeter, as indicated by the user input, of the object represented in the acquired image. For instance, when an estimated perimeter of the selected object, as represented in the acquired image on a display, is partially or entirely incorrect (e.g., due to insufficient lighting or the presence of numerous objects when the image is acquired), the user may modify the estimated perimeter so that dimensional data for the selected object is computed not based on incorrect information (e.g., incorrect estimated perimeter) but based on modified information.


In one embodiment, the user is notified of the initial selection of the initially selected one object by a display of the acquired image, where the initially selected one object is visually distinguished in the display of the acquired image from any other objects represented in the display of the acquired image. In one embodiment, the initially selected one object is visually distinguished from any other objects represented in the display of the acquired image with a display of a border about at least a portion of the initially selected object in the display of the acquired image. In such a case, in an embodiment, the at least one user input received may include at least one signal representing a position in the image that indicates a position of at least a portion of a new perimeter for the object for processing. In an alternative embodiment, the initially selected one object is visually distinguished from any other objects represented in the display of the acquired image with a display of a draggable border about at least a portion of the initially selected object in the display of the acquired image. For example, the at least one user input received may include at least one signal representing a dragging of the draggable border to a new position that indicates at least a portion of a new perimeter for the object for processing.


It should be appreciated by one skilled in the art that the process 30a may be implemented in one integrated device or in multiple standalone devices. For example, the process 30a may be implemented in any of the computing system 10a, 10b, and 10c of FIGS. 1A-1C, and the process 30a may be implemented in the electronic device 20a of FIG. 2A or in the electronic device 20b or FIG. 2B.



FIG. 3B shows a flow chart of a process 30b of operating a dimensioning system to determine dimensional information for objects according to one non-limiting illustrated embodiment. In one embodiment, at 31b, a number of images is captured or acquired. At 32b, objects or spaces in at least one of the acquired images are computationally identified, for example, by a processor-based system or a computing system. At 33b, the dimensional data for at least one object or space is determined. In one embodiment, a processor-based system or a computing system automatically selects an object or space in an acquired image and computes a dimensional data for the selected object or space without any human interaction. At least one user input indicative of an object or space selected for processing is received at 34b. In one embodiment, the user input may indicate an agreement with the selection of the object or space for which a dimensional data is determined. In another embodiment, the user input may select a different object or space for which a dimensional data is to be determined.


The process 30b may further computationally determine dimensional data for the object or space selected by the received user input at 35b. For example, in one embodiment, this may be due to the user input selecting an object or space that is different from the object or space for which a dimensional data has been determined. The process 30b may further computationally revise the determined dimensional data for the at least one object or space in response to the received user input at 36b. For example, in one embodiment, the user may agree with the selection of the object or space but disagree with the certain aspect of the selection (e.g., the border of the selected object or space which is used to determine the volume of the object or space). In such case, the user input may be a modification to that aspect of the selection of the object or space, such as, for example, a change in the selected object's or space's border.


The user input may come in different forms. For example, the user input may be a keyboard entry on a keyboard, a click or “click and drag” using a computer mouse, entry through a touch-sensitive screen by the user's finger or a stylus or similar tool, a voice command including at least one command word, an audible command such as a clap or some recognizable sound, or entry by a bar code reader.


As with the process 30a, the process 30b may be implemented in one integrated device or in multiple standalone devices. For example, the process 30b may be implemented in any of the computing system 10a, 10b, and 10c of FIGS. 1A-1C, and the process 30b may be implemented in the electronic device 20a of FIG. 2A or in the electronic device 20b or FIG. 2B.



FIG. 4A shows a flow chart of a process 40a of selecting an object from at least one object in an image to process information about the selected object according to one non-limiting illustrated embodiment. In one embodiment, at 41a, an image of the at least one object is provided. At 42a, a first object of the at least one object in the image is selected. For example, a computing system executing the process 40a may be configured to automatically select the first object of the at least one object in the image without any human interaction. The image is updated to indicate the selection of the first object at 43a. At 44a, an input related to the selection of the first object is received. The image is then updated to indicate the input at 45a. At 46a, dimensional data related to one of the at least one object is computationally determined using the input.


In one embodiment, the image is updated to indicate an estimated perimeter around the first object when updating the image to indicate the selection of the first object. In one embodiment, the input (e.g., a user input manually entered by a user) selects a second object different than the first object. In another embodiment, the input modifies an aspect related to the indication of the selection of the first object. For example, in an embodiment, one aspect related to the indication of the selection of the first object may be an estimated perimeter of the first object as shown in the image, and accordingly the input may modify the estimated perimeter of the first object.


In some embodiments, the input may be a mark or a line drawn on, for example, a touch-screen device by a user to either validate the selection of the first object or to select a second object different than the first object. The input may also be a user input to point out corners of the first object in the image on, for example, a touch-screen device. When an estimated perimeter of the first object is also indicated in the image, the input may be a user input to correct a corner position of the estimated perimeter by moving a corner point of the first object in the image on, say, a touch-screen device. The estimated perimeter of the first object may be a draggable perimeter displayed on a display device and modifiable by a user dragging at least a portion of the estimated perimeter (e.g., in a click-and-drag or point-and-drag fashion) to change the estimated perimeter into a modified boundary that more closely resembles the real perimeter of the first object. Alternatively, the input may be a boundary line drawn by the user to indicate the selection of an object approximately surrounded by the line drawn by the user. As indicated previously, the input may be done by using the user's finger, a stylus or similar tool, by using a keyboard, or by using a computer mouse.


Accordingly, in one embodiment, the input received may be a user selection on a portion of a touch-screen device to select a second object of the at least one object. In another embodiment, the input received may be a boundary drawn on a touch-screen device around an image of a second object of the at least one object to select the second object that is different than the first object. In one embodiment, receiving an input may include detecting a number of contacts at a number of positions on a touch-screen device where the contacts indicate a number of corners of the first object. In a different embodiment, the received input may include at least one user input indicative of a new position of a corner of the first object in the image displayed on a touch-screen device. Alternatively, the received input may include at least one user input indicative of a perimeter of one of the at least one object on a touch-screen device indicative of a selection of the selected object.


In one embodiment, determining dimensional data related to one of the at least one object using the input may include determining a dimensional weight of the one of the at least one object based on a computationally determined estimated perimeter of the one of the at least one object. For instance, when the user input confirms the initial selection of the first object by a computing system, the computing system will determine the dimensional weight of the first object based on the estimated perimeter as determined by the computing system. In an alternative embodiment, determining dimensional data related to one of the at least one object using the input may include determining a dimensional weight of the one of the at least one object based on a user identified perimeter of the one of the at least one object. For example, when the user input modifies an estimated perimeter of the first object as determined by the computing system, the computing system determines the dimensional weight of the first object based on the modified perimeter. If the user input instead selects a second object that is not the first object, the computing system may determine the dimensional weight of the user-selected second object based on an estimated perimeter of the second object as determined by the computing system or based on a user-identified perimeter of the second object.


It should be appreciated by one skilled in the art that the process 40a may be implemented in one integrated device or in multiple standalone devices. For example, the process 40a may be implemented in any of the computing system 10a, 10b, and 10c of FIGS. 1A-1C, and the process 40a may be implemented in the electronic device 20a of FIG. 2A or in the electronic device 20b or FIG. 2B.



FIG. 4B shows a flow chart of a process 40b of selecting an object from at least one object in an image to process information about the selected object according to one non-limiting illustrated embodiment. In one embodiment, at 41b, the image of the at least one object is displayed. At 42b, a first object of the at least one object in the image is selected. For example, a processor-based system or a computing system executing the process 40b may be configured to automatically select the first object of the at least one object in the image without any human interaction. The image is updated to indicate the selection of the first object at 43b. At 44b, an input related to the selection of the first object is received. The image is updated to indicate the input at 45b. In one embodiment, the process 40b may further computationally determine dimensional data related to one of the at least one object using the input at 46b.


As with the process 40a, the process 40b may be implemented in one integrated device or in multiple standalone devices. For example, the process 40b may be implemented in any of the computing system 10a, 10b, and 10c of FIGS. 1A-1C, and the process 40b may be implemented in the electronic device 20a of FIG. 2A or in the electronic device 20b or FIG. 2B.



FIG. 5A shows a flow chart of a process 50a performed by instructions (e.g., a computer-executable program) stored in a computer-readable medium according to one non-limiting illustrated embodiment. In one embodiment, the process 50a may be instructions in the form of a software program stored in a compact disc (CD), a memory device such as a universal serial bus (USB) memory device or a memory chip of a computing device. Accordingly, the process 50a may be executed by a device, such as a computer, that reads the instruction. In one embodiment, an image is displayed at 51a. At 52a, objects represented in the acquired image are identified. At 53a, one object of the objects represented in the acquired image is initially selected for processing. At 54a, the acquired image and an indication indicative of the initially selected one object are displayed. User input is received at 55a. At 56a, dimensional data for the object indicated by at least one user input is determined.


In one embodiment, determining dimensional data for the object indicated by at least one user input may include determining a dimensional weight based on an estimated perimeter of the initially selected one object as represented in the acquired image in response to at least one user input confirming the initially selected one object as the object to be processed. For example, when a user confirms the estimated perimeter of initially selected object A, the dimensional weight of object A is determined based on the estimated perimeter. Alternatively, determining dimensional data for the object indicated by at least one user input may include determining a dimensional weight based on a new perimeter of the initially selected one object represented in the acquired image in response to at least one user input indicative of the new perimeter. For example, when a user modifies an estimated perimeter of initially selected object A to form a new perimeter, the dimensional weight of object A is determined based on the new perimeter.


In one embodiment, determining dimensional data for the object indicated by at least one user input may include determining a dimensional weight based on an estimated perimeter of an object represented in the acquired image other than the initially selected one object in response to at least one user input selecting the other object as the object to be processed. For example, when the user selects object B, which is different than object A as initially selected by the computer-executable program, the dimensional weight of object B may be determined based on an estimated perimeter of object B as determined by the program. In another embodiment, determining dimensional data for the object indicated by at least one user input may include determining a dimensional weight based on a user identified perimeter of an object represented in the acquired image other than the initially selected one object in response to at least one user input selecting the other object as the object to be processed and identifying at least a portion of the user identified perimeter. For instance, when the user selects object B and identifies a user-identified perimeter of object B, the dimensional weight of object B may be determined based on the user-identified perimeter. The user-identified perimeter may also be displayed as a feedback to the user on a display of the acquired image to acknowledge the user input.


In one embodiment, causing the acquired image and an indication indicative of the initially selected one object to be displayed may include causing the acquired image to be displayed and causing a draggable border about at least a portion of the initially selected one object to be displayed in a display of the acquired image. In another embodiment, causing the acquired image and an indication indicative of the initially selected one object to be displayed may include causing the acquired image to be displayed and causing a draggable border about at least a portion of a user selected object to be displayed in a display of the acquired image. In either case, with the draggable border displayed, a user may drag the draggable border to make modifications to correct error in the displayed border.



FIG. 5B shows a flow chart of a process 50b. Similar to the process 50a, the process 50b may be performed by instructions (e.g., a computer-executable program) stored in a computer-readable medium according to one non-limiting illustrated embodiment. In one embodiment, the process 50b may be instructions in the form of a software program stored in a CD, a memory device such as a USB memory device or a memory chip of a computing device. Accordingly, the process 50b may be executed by a device, such as a computer, that reads the instruction. In one embodiment, an image is displayed at 51b. At 52b, objects or spaces represented in the displayed image are identified. At 53b, an indication is provided to a user. For example, an indication that one of the objects or spaces in the displayed image is automatically selected for further processing, e.g., to determine a dimensional data related to the selected object or space. User input is received at 54b. At 55b, dimensional data for an object or space is determined in response to the user input. For example, if the user input confirms the selection of the object or space, then dimensional data related to the selected object or space is determined. On the other hand, if the user input selects a different object or space than the one automatically selected, then dimensional data of the user selected object or space is determined. Alternatively, if the user input modifies an aspect related to the selection of the automatically selected object or space, such as the border of the object or space, then dimensional data of the automatically selected object or space is determined based on the user-modified border, for instance.


In one embodiment, the process 50b may further determine dimensional data for one of the identified objects or spaces in the displayed image prior to receiving the user input at 56b. In another embodiment, the process 50b may further display a dimensional data for an object or space. For example, a dimensional data, such as length, width, height, area, or volume, of the automatically selected object or space may be displayed before and/or after the user input is received. In yet another embodiment, at 57b, the process 50b may display a second image after receiving the user input. Objects or spaces represented in the second image are identified at 58b. Another user input is received at 59b.



FIG. 6A shows an image of two objects as taken by, for example, the imager 15 of the dimensioning system 10 or the imager 25 of the electronic device 20, according to one non-limiting illustrated embodiment. In this example, there are two objects, i.e., parcels, in the image.



FIG. 6B shows the image of the two objects of FIG. 6A and an indication of the selection of one of the two objects according to one embodiment. For example, after the computing system 12 of the dimensioning system 10 or the processing component 22 of the electronic device 20 automatically selects the parcel on the left in the image, the computing system 12 or the processing component 22 causes the selection of the parcel on the left to be shown in the image as well. This way, a user using the dimensioning system 10 or the electronic device 20 is informed of the automatic selection of the parcel on the left. In the example shown in FIG. 6B, the indication that the parcel on the left has been selected is presented as an estimated perimeter around the selected parcel. Further, the indication may also include lines showing the estimated edges of the selected parcel, as can be seen in FIG. 6B. The estimation of the perimeter and edges of a selected object is done by using pertinent algorithm with the image of the objects as known in the art.



FIG. 6C shows the image of the two objects of FIG. 6A, an indication that the parcel on the left has been automatically selected, and an indication of a user selection of the parcel on the right according to one embodiment. FIG. 6D shows the image of the two objects of FIG. 6A, an indication that the parcel on the left has been automatically selected, and an indication of a user selection of the parcel on the right according to another embodiment. In one embodiment, a user of the dimensioning system 10 or the electronic device 20 may override, or correct, the automatic selection by making a user input to select the parcel that should have been selected by the automatic process. The user may make such selection in one of many ways. For example, as shown in FIG. 6C, the user may draw a check mark on the desired object, i.e., the parcel on the right, with a stylus on the touch screen of, say, a handheld device to select the parcel on the right. Alternatively, the user may circle or box the parcel on the right with a stylus on the touch screen of the handheld device, as shown in FIG. 6D. The user may also make his/her selection by drawing a cross on the object of choice, placing a cursor on the object of choice and clicking on a computer mouse, or making selection via a keyboard, for example.



FIG. 6E shows an image of two parcels and an indication of an estimated perimeter of the parcel on the right according to one embodiment. In the example shown, the system did not correctly detect the borders of the selected object, i.e., the parcel on the right, and thus the estimated perimeter shown in the image is not entirely correct. This may be due to poor contrast as a result of insufficient lighting when the image was captured. FIG. 6F shows an example of a user modification of the estimated perimeter of the parcel on the right of FIG. 6E according to one embodiment. In one embodiment, the user may make the correction by selecting a corner and moving this corner to its proximate correct position. In an embodiment, the user may point directly the correct location, e.g., by tapping a touch screen with a stylus or the user's finger, to modify the perimeter. Alternatively, the user may approximately draw the correct borders of the object, either entirely or only where the estimation is incorrect, to make the correction.


Thus, systems and methods to allow user interaction in volume dimensioning an object are disclosed herein and should greatly improve upon the inaccuracy problem described above. For instance, when a dimensioning application selects an incorrect object for dimensioning or when the estimated perimeter of the selected object is erroneous, a user can intervene by selecting the correct object for dimensioning or by modifying the estimated perimeter. This user interaction provides a way for the user to validate or modify selections made by the application, and thereby avoid inaccuracies that might arise if the process is fully automated.


The above description of illustrated embodiments, including what is described in the Abstract, is not intended to be exhaustive or to limit the embodiments to the precise forms disclosed. Although specific embodiments of and examples are described herein for illustrative purposes, various equivalent modifications can be made without departing from the spirit and scope of the disclosure, as will be recognized by those skilled in the relevant art. The teachings provided herein of the various embodiments can be applied to other context, not necessarily the exemplary context of volume dimensioning generally described above. It will be understood by those skilled in the art that, although the embodiments described above and shown in the figures are generally directed to the context of volume dimensioning, applications for determining other values related to objects, such as parcels and packages, may also benefit from the concepts described herein. Further, although the embodiments described above and shown in the figures are directed to volume dimensioning using a portable electronic device, the concepts and the embodiments described herein are equally applicable to non-portable devices or to a system having multiple standalone devices coupled to one.


These and other changes can be made to the embodiments in light of the above-detailed description. In general, in the following claims, the terms used should not be construed to limit the claims to the specific embodiments disclosed in the specification and the claims, but should be construed to include all possible embodiments along with the full scope of equivalents to which such claims are entitled. Accordingly, the claims are not limited by the disclosure.

Claims
  • 1. A dimensioning system, comprising: an imager configured to acquire images;a user input/output system configured to display images and to receive user input; anda processor configured to:identify representations of three-dimensional objects in the acquired images;initially select one of the identified objects;display the acquired images and an indication indicative of the initially selected one object via the user input/output system;receive a first indication of at least one user input via the user input/output system, the first indication of the at least one user input comprising an indication of a user-selected object to override the selection by the processor of the initially selected one object, the user-selected object being an object other than the initially selected one object, ora second indication of at least one user input via the user input/output system, the second indication of the at least one user input comprising an indication confirming the selection by the processor of the initially selected one object; andcomputationally determine dimensional weight data for the user-selected object if the processor receives the first indication of the at least one user input via the user input/output system comprising an indication of the user-selected object, orthe initially selected one object if the processor receives the second indication of the at least one user input comprising an indication confirming the selection by the processor.
  • 2. The dimensioning system of claim 1, wherein the processor is configured to, in response receiving the second indication, determine the dimensional weight of the initially selected one object based on an estimated perimeter of the initially selected one object.
  • 3. The dimensioning system of claim 1, wherein the processor is configured to, in response to at least one user input indicative of a new perimeter for the initially selected one object, determine a dimensional weight based on the new perimeter of the initially selected one object.
  • 4. The dimensioning system of claim 1, wherein the processor is configured to, in response to receiving the first indication, determine the dimensional weight of the user-selected object based on an estimated perimeter of the user-selected object.
  • 5. The dimensioning system of claim 1, wherein the processor is configured to, in response to at least one user input (i) indicative of the user-selected object and (ii) identifying at least a portion of a perimeter of the user-selected object, determine the dimensional weight of the user-selected object based on the user identified perimeter of the user-selected object.
  • 6. The dimensioning system of claim 1, wherein the indication indicative of the initially selected one object comprises a draggable border about at least a portion of the initially selected object.
  • 7. The dimensioning system of claim 1, wherein the processor is configured to, in response to receiving the first indicator, displaying, via the user input/output system, a draggable border about at least a portion of the user-selected object.
  • 8. The dimensioning system of claim 1, wherein the processor is configured to display, via the user input/output system, dimensional data for one or more objects in the acquired images.
  • 9. The dimensioning system of claim 1, wherein the processor is configured to revise the computationally determined dimensional weight data in response to receiving the at least one user input and/or at least one additional user input received via the user input/output system.
  • 10. The dimensioning system of claim 1, wherein the processor is configured to computationally determine dimensional weight data for the initially selected one of the identified objects prior to receiving the at least one user input via the user input/output system.
  • 11. A processor-implemented method, comprising: acquiring images via an imager;identifying representations of three-dimensional objects in the acquired images;selecting an initially selected one object of the identified objects;displaying the acquired images and an indication indicative of the initially selected one object via a user input/output system;receiving a first indication of at least one user input via the user input/output system, the first indication of the at least one user input comprising an indication of a user-selected object to override the selection by the processor of the initially selected one object, the user-selected object being an object other than the initially selected one object, ora second indication of at least one user input via the user input/output system, the second indication of the at least one user input comprising an indication confirming the selection by the processor of the initially selected one object; andcomputationally determining dimensional weight data for the user-selected object if receiving the first indication of the at least one user input comprising an indication of the user-selected object, orthe initially selected one object if receiving the second indication of the at least one user input comprising an indication confirming the selection by the processor.
  • 12. The method of claim 11, comprising, in response to receiving the second indication, determining the dimensional weight of the initially selected one object based on an estimated perimeter of the initially selected one object.
  • 13. The method of claim 11, comprising, in response to at least one user input indicative of a new perimeter for the initially selected one object, determining a dimensional weight based on the new perimeter of the initially selected one object.
  • 14. The method of claim 11, comprising, in response to receiving the first indication, determining the dimensional weight of the user-selected object based on an estimated perimeter of the user-selected object.
  • 15. The method of claim 11, comprising, in response to at least one user input (i) indicative of the user-selected object and (ii) identifying at least a portion of a perimeter of the user-selected object, determining the dimensional weight of the user-selected object based on the user identified perimeter of the user-selected object.
  • 16. The method of claim 11, wherein the indication indicative of the initially selected one object comprises a draggable border about at least a portion of the initially selected object.
  • 17. The method of claim 11, comprising, in response to receiving the first indication, displaying, via the user input/output system, a draggable border about at least a portion of the user-selected object.
  • 18. The method of claim 11, comprising, displaying, via the user input/output system, dimensional data for one or more objects in the acquired images.
  • 19. The method of claim 11, comprising revising the computationally determined dimensional weight data in response to receiving the at least one user input and/or at least one additional user input received via the user input/output system.
  • 20. The method of claim 11, comprising computationally determining dimensional weight data for the initially selected one of the identified objects prior to receiving the at least one user input via the user input/output system.
Priority Claims (1)
Number Date Country Kind
09368001 Jan 2009 EP regional
CROSS REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit of U.S. patent application Ser. No. 12/685,816 for Semi-Automatic Dimensioning with Imager on a Portable Device filed Jan. 12, 2010 (and published Aug. 12, 2010 as U.S. Patent Application Publication No. 2010/0202702), now U.S. Pat. No. 8,908,995, which claims the benefit of U.S. Patent Application No. 61/149,912 for Semi-Automatic Dimensioning with Imager on a Portable Device filed Feb. 4, 2009. Each of the foregoing patent applications, patent publication, and patent is hereby incorporated by reference in its entirety.

US Referenced Citations (857)
Number Name Date Kind
3971065 Bayer Jul 1976 A
4279328 Ahlbom Jul 1981 A
4398811 Nishioka et al. Aug 1983 A
4495559 Gelatt, Jr. Jan 1985 A
4730190 Win et al. Mar 1988 A
4803639 Steele et al. Feb 1989 A
4974919 Muraki et al. Dec 1990 A
5111325 DeJager May 1992 A
5175601 Fitts Dec 1992 A
5184733 Arnarson Feb 1993 A
5220536 Stringer et al. Jun 1993 A
5243619 Albers et al. Sep 1993 A
5331118 Jensen Jul 1994 A
5359185 Hanson Oct 1994 A
5384901 Glassner et al. Jan 1995 A
5548707 LoNegro et al. Aug 1996 A
5555090 Schmutz Sep 1996 A
5561526 Huber Oct 1996 A
5590060 Granville et al. Dec 1996 A
5592333 Lewis Jan 1997 A
5606534 Stringer et al. Feb 1997 A
5619245 Kessler et al. Apr 1997 A
5655095 LoNegro et al. Aug 1997 A
5661561 Wurz et al. Aug 1997 A
5699161 Woodworth Dec 1997 A
5729750 Ishida Mar 1998 A
5730252 Herbinet Mar 1998 A
5732147 Tao Mar 1998 A
5734476 Dlugos Mar 1998 A
5737074 Raga et al. Apr 1998 A
5748199 Palm May 1998 A
5767962 Suzuki et al. Jun 1998 A
5802092 Endriz Sep 1998 A
5808657 Kurtz et al. Sep 1998 A
5831737 Stringer et al. Nov 1998 A
5850370 Stringer et al. Dec 1998 A
5850490 Johnson Dec 1998 A
5869827 Rando Feb 1999 A
5870220 Migdal et al. Feb 1999 A
5900611 Hecht May 1999 A
5923428 Woodworth Jul 1999 A
5929856 LoNegro et al. Jul 1999 A
5938710 Lanza et al. Aug 1999 A
5959568 Woolley Sep 1999 A
5960098 Tao Sep 1999 A
5969823 Wurz et al. Oct 1999 A
5978512 Kim et al. Nov 1999 A
5979760 Freyman et al. Nov 1999 A
5988862 Kacyra et al. Nov 1999 A
5991041 Woodworth Nov 1999 A
6009189 Schaack Dec 1999 A
6025847 Marks Feb 2000 A
6049386 Stringer et al. Apr 2000 A
6053409 Brobst et al. Apr 2000 A
6064759 Buckley et al. May 2000 A
6067110 Nonaka et al. May 2000 A
6069696 McQueen et al. May 2000 A
6115114 Berg Sep 2000 A
6137577 Woodworth Oct 2000 A
6177999 Wurz et al. Jan 2001 B1
6189223 Haug Feb 2001 B1
6232597 Kley May 2001 B1
6236403 Chaki May 2001 B1
6246468 Dimsdale Jun 2001 B1
6333749 Reinhardt et al. Dec 2001 B1
6336587 He et al. Jan 2002 B1
6369401 Lee Apr 2002 B1
6373579 Ober et al. Apr 2002 B1
6429803 Kumar Aug 2002 B1
6457642 Good et al. Oct 2002 B1
6507406 Yagi et al. Jan 2003 B1
6517004 Good et al. Feb 2003 B2
6519550 D'Hooge et al. Feb 2003 B1
6535776 Tobin et al. Mar 2003 B1
6661521 Stern Dec 2003 B1
6674904 McQueen Jan 2004 B1
6705526 Zhu et al. Mar 2004 B1
6773142 Rekow Aug 2004 B2
6781621 Gobush et al. Aug 2004 B1
6804269 Lizotte et al. Oct 2004 B2
6824058 Patel et al. Nov 2004 B2
6832725 Gardiner et al. Dec 2004 B2
6858857 Pease et al. Feb 2005 B2
6922632 Foxlin Jul 2005 B2
6971580 Zhu et al. Dec 2005 B2
6995762 Pavlidis et al. Feb 2006 B1
7057632 Yamawaki et al. Jun 2006 B2
7085409 Sawhney et al. Aug 2006 B2
7086162 Tyroler Aug 2006 B2
7104453 Zhu et al. Sep 2006 B1
7128266 Marlton et al. Oct 2006 B2
7137556 Bonner Nov 2006 B1
7159783 Walczyk et al. Jan 2007 B2
7161688 Bonner et al. Jan 2007 B1
7205529 Andersen Apr 2007 B2
7214954 Schopp May 2007 B2
7233682 Levine Jun 2007 B2
7277187 Smith et al. Oct 2007 B2
7307653 Dutta Dec 2007 B2
7310431 Gokturk et al. Dec 2007 B2
7413127 Ehrhart et al. Aug 2008 B2
7527205 Zhu et al. May 2009 B2
7586049 Wurz Sep 2009 B2
7602404 Reinhardt et al. Oct 2009 B1
7614563 Nunnink et al. Nov 2009 B1
7639722 Paxton et al. Dec 2009 B1
7726575 Wang et al. Jun 2010 B2
7780084 Zhang et al. Aug 2010 B2
7788883 Buckley et al. Sep 2010 B2
7974025 Topliss Jul 2011 B2
8009358 Zalevsky et al. Aug 2011 B2
8027096 Feng et al. Sep 2011 B2
8028501 Buckley et al. Oct 2011 B2
8050461 Shpunt et al. Nov 2011 B2
8055061 Katano Nov 2011 B2
8061610 Nunnink Nov 2011 B2
8072581 Breiholz Dec 2011 B1
8102395 Kondo et al. Jan 2012 B2
8132728 Dwinell et al. Mar 2012 B2
8134717 Pangrazio et al. Mar 2012 B2
8149224 Kuo et al. Apr 2012 B1
8194097 Xiao et al. Jun 2012 B2
8212889 Chanas et al. Jul 2012 B2
8224133 Popovich et al. Jul 2012 B2
8228510 Pangrazio et al. Jul 2012 B2
8230367 Bell Jul 2012 B2
8294969 Plesko Oct 2012 B2
8301027 Shaw et al. Oct 2012 B2
8305458 Hara Nov 2012 B2
8310656 Zalewski Nov 2012 B2
8313380 Zalewski et al. Nov 2012 B2
8317105 Kotlarsky et al. Nov 2012 B2
8320621 McEldowney Nov 2012 B2
8322622 Suzhou et al. Dec 2012 B2
8339462 Stec et al. Dec 2012 B2
8350959 Topliss et al. Jan 2013 B2
8351670 Ijiri et al. Jan 2013 B2
8366005 Kotlarsky et al. Feb 2013 B2
8371507 Haggerty et al. Feb 2013 B2
8374498 Pastore Feb 2013 B2
8376233 Van Horn et al. Feb 2013 B2
8381976 Mohideen et al. Feb 2013 B2
8381979 Franz Feb 2013 B2
8390909 Plesko Mar 2013 B2
8408464 Zhu et al. Apr 2013 B2
8408468 Horn et al. Apr 2013 B2
8408469 Good Apr 2013 B2
8424768 Rueblinger et al. Apr 2013 B2
8437539 Komatsu et al. May 2013 B2
8441749 Brown et al. May 2013 B2
8448863 Xian et al. May 2013 B2
8457013 Essinger et al. Jun 2013 B2
8459557 Havens et al. Jun 2013 B2
8463079 Ackley et al. Jun 2013 B2
8469272 Kearney Jun 2013 B2
8474712 Kearney et al. Jul 2013 B2
8479992 Kotlarsky et al. Jul 2013 B2
8490877 Kearney Jul 2013 B2
8517271 Kotlarsky et al. Aug 2013 B2
8523076 Good Sep 2013 B2
8528818 Ehrhart et al. Sep 2013 B2
8544737 Gomez et al. Oct 2013 B2
8548420 Grunow et al. Oct 2013 B2
8550335 Samek et al. Oct 2013 B2
8550354 Gannon et al. Oct 2013 B2
8550357 Kearney Oct 2013 B2
8556174 Kosecki et al. Oct 2013 B2
8556176 Van Horn et al. Oct 2013 B2
8556177 Hussey et al. Oct 2013 B2
8559767 Barber et al. Oct 2013 B2
8561895 Gomez et al. Oct 2013 B2
8561903 Sauerwein Oct 2013 B2
8561905 Edmonds et al. Oct 2013 B2
8565107 Pease et al. Oct 2013 B2
8570343 Halstead Oct 2013 B2
8571307 Li et al. Oct 2013 B2
8576390 Nunnink Nov 2013 B1
8579200 Samek et al. Nov 2013 B2
8583924 Caballero et al. Nov 2013 B2
8584945 Wang et al. Nov 2013 B2
8587595 Wang Nov 2013 B2
8587697 Hussey et al. Nov 2013 B2
8588869 Sauerwein et al. Nov 2013 B2
8590789 Nahill et al. Nov 2013 B2
8596539 Havens et al. Dec 2013 B2
8596542 Havens et al. Dec 2013 B2
8596543 Havens et al. Dec 2013 B2
8599271 Havens et al. Dec 2013 B2
8599957 Peake et al. Dec 2013 B2
8600158 Li et al. Dec 2013 B2
8600167 Showering Dec 2013 B2
8602309 Longacre et al. Dec 2013 B2
8608053 Meier et al. Dec 2013 B2
8608071 Liu et al. Dec 2013 B2
8611309 Wang et al. Dec 2013 B2
8615487 Gomez et al. Dec 2013 B2
8621123 Caballero Dec 2013 B2
8622303 Meier et al. Jan 2014 B2
8628013 Ding Jan 2014 B2
8628015 Wang et al. Jan 2014 B2
8628016 Winegar Jan 2014 B2
8629926 Wang Jan 2014 B2
8630491 Longacre et al. Jan 2014 B2
8635309 Berthiaume et al. Jan 2014 B2
8636200 Kearney Jan 2014 B2
8636212 Nahill et al. Jan 2014 B2
8636215 Ding et al. Jan 2014 B2
8636224 Wang Jan 2014 B2
8638806 Wang et al. Jan 2014 B2
8640958 Lu et al. Feb 2014 B2
8640960 Wang et al. Feb 2014 B2
8643717 Li et al. Feb 2014 B2
8646692 Meier et al. Feb 2014 B2
8646694 Wang et al. Feb 2014 B2
8657200 Ren et al. Feb 2014 B2
8659397 Vargo et al. Feb 2014 B2
8668149 Good Mar 2014 B2
8678285 Kearney Mar 2014 B2
8678286 Smith et al. Mar 2014 B2
8682077 Longacre Mar 2014 B1
D702237 Oberpriller et al. Apr 2014 S
8687282 Feng et al. Apr 2014 B2
8692927 Pease et al. Apr 2014 B2
8695880 Bremer et al. Apr 2014 B2
8698949 Grunow et al. Apr 2014 B2
8702000 Barber et al. Apr 2014 B2
8717494 Gannon May 2014 B2
8720783 Biss et al. May 2014 B2
8723804 Fletcher et al. May 2014 B2
8723904 Marty et al. May 2014 B2
8727223 Wang May 2014 B2
8740082 Wilz Jun 2014 B2
8740085 Furlong et al. Jun 2014 B2
8746563 Hennick et al. Jun 2014 B2
8750445 Peake et al. Jun 2014 B2
8752766 Xian et al. Jun 2014 B2
8756059 Braho et al. Jun 2014 B2
8757495 Qu et al. Jun 2014 B2
8760563 Koziol et al. Jun 2014 B2
8736909 Reed et al. Jul 2014 B2
8777108 Coyle Jul 2014 B2
8777109 Oberpriller et al. Jul 2014 B2
8779898 Havens et al. Jul 2014 B2
8781520 Payne et al. Jul 2014 B2
8783573 Havens et al. Jul 2014 B2
8789757 Barten Jul 2014 B2
8789758 Hawley et al. Jul 2014 B2
8789759 Xian et al. Jul 2014 B2
8792688 Unsworth Jul 2014 B2
8794520 Wang et al. Aug 2014 B2
8794522 Ehrhart Aug 2014 B2
8794525 Amundsen et al. Aug 2014 B2
8794526 Wang et al. Aug 2014 B2
8798367 Ellis Aug 2014 B2
8807431 Wang et al. Aug 2014 B2
8807432 Van Horn et al. Aug 2014 B2
8810779 Hilde Aug 2014 B1
8820630 Qu et al. Sep 2014 B2
8822848 Meagher Sep 2014 B2
8824692 Sheerin et al. Sep 2014 B2
8824696 Braho Sep 2014 B2
8842849 Wahl et al. Sep 2014 B2
8844822 Kotlarsky et al. Sep 2014 B2
8844823 Fritz et al. Sep 2014 B2
8849019 Li et al. Sep 2014 B2
D716285 Chaney et al. Oct 2014 S
8851383 Yeakley et al. Oct 2014 B2
8854633 Laffargue Oct 2014 B2
8866963 Grunow et al. Oct 2014 B2
8868421 Braho et al. Oct 2014 B2
8868519 Maloy et al. Oct 2014 B2
8868802 Barten Oct 2014 B2
8868803 Bremer et al. Oct 2014 B2
8870074 Gannon Oct 2014 B1
8879639 Sauerwein Nov 2014 B2
8880426 Smith Nov 2014 B2
8881983 Havens et al. Nov 2014 B2
8881987 Wang Nov 2014 B2
8897596 Passmore et al. Nov 2014 B1
8903172 Smith Dec 2014 B2
8908277 Pesach et al. Dec 2014 B2
8908995 Benos Dec 2014 B2
8910870 Li et al. Dec 2014 B2
8910875 Ren et al. Dec 2014 B2
8914290 Hendrickson et al. Dec 2014 B2
8914788 Pettinelli et al. Dec 2014 B2
8915439 Feng et al. Dec 2014 B2
8915444 Havens et al. Dec 2014 B2
8916789 Woodburn Dec 2014 B2
8918250 Hollifield Dec 2014 B2
8918564 Caballero Dec 2014 B2
8925818 Kosecki et al. Jan 2015 B2
8939374 Jovanovski et al. Jan 2015 B2
8942480 Ellis Jan 2015 B2
8944313 Williams et al. Feb 2015 B2
8944327 Meier et al. Feb 2015 B2
8944332 Harding et al. Feb 2015 B2
8950678 Germaine et al. Feb 2015 B2
D723560 Zhou et al. Mar 2015 S
8967468 Gomez et al. Mar 2015 B2
8971346 Sevier Mar 2015 B2
8976030 Cunningham et al. Mar 2015 B2
8976368 Akel et al. Mar 2015 B2
8978981 Guan Mar 2015 B2
8978983 Bremer et al. Mar 2015 B2
8978984 Hennick et al. Mar 2015 B2
8985456 Zhu et al. Mar 2015 B2
8985457 Soule et al. Mar 2015 B2
8985459 Kearney et al. Mar 2015 B2
8985461 Gelay et al. Mar 2015 B2
8988578 Showering Mar 2015 B2
8988590 Gillet et al. Mar 2015 B2
8991704 Hopper et al. Mar 2015 B2
8993974 Goodwin Mar 2015 B2
8996194 Davis et al. Mar 2015 B2
8996384 Funyak et al. Mar 2015 B2
8998091 Edmonds et al. Apr 2015 B2
9002641 Showering Apr 2015 B2
9007368 Laffargue et al. Apr 2015 B2
9010641 Qu et al. Apr 2015 B2
9014441 Truyen Apr 2015 B2
9015513 Murawski et al. Apr 2015 B2
9016576 Brady et al. Apr 2015 B2
D730357 Fitch et al. May 2015 S
9022288 Nahill et al. May 2015 B2
9030964 Essinger et al. May 2015 B2
9033240 Smith et al. May 2015 B2
9033242 Gillet et al. May 2015 B2
9036054 Koziol et al. May 2015 B2
9037344 Chamberlin May 2015 B2
9038911 Xian et al. May 2015 B2
9038915 Smith May 2015 B2
D730901 Oberpriller et al. Jun 2015 S
D730902 Fitch et al. Jun 2015 S
D733112 Chaney et al. Jun 2015 S
9047098 Barten Jun 2015 B2
9047359 Caballero et al. Jun 2015 B2
9047420 Caballero Jun 2015 B2
9047525 Barber Jun 2015 B2
9047531 Showering et al. Jun 2015 B2
9049640 Wang et al. Jun 2015 B2
9053055 Caballero Jun 2015 B2
9053378 Hou et al. Jun 2015 B1
9053380 Xian et al. Jun 2015 B2
9057641 Amundsen et al. Jun 2015 B2
9058526 Powilleit Jun 2015 B2
9064165 Havens et al. Jun 2015 B2
9064167 Xian et al. Jun 2015 B2
9064168 Todeschini et al. Jun 2015 B2
9064254 Todeschini et al. Jun 2015 B2
9066032 Wang Jun 2015 B2
9066087 Shpunt Jun 2015 B2
9070032 Corcoran Jun 2015 B2
D734339 Zhou et al. Jul 2015 S
D734751 Oberpriller et al. Jul 2015 S
9082023 Feng et al. Jul 2015 B2
9082195 Holeva et al. Jul 2015 B2
9142035 Rotman et al. Sep 2015 B1
9233470 Bradski et al. Jan 2016 B1
9273846 Rossi et al. Mar 2016 B1
9299013 Curlander et al. Mar 2016 B1
9366861 Johnson Jun 2016 B1
9424749 Reed et al. Aug 2016 B1
9486921 Straszheim et al. Nov 2016 B1
9736459 Mor et al. Aug 2017 B2
9828223 Svensson et al. Nov 2017 B2
20010027995 Patel et al. Oct 2001 A1
20010032879 He et al. Oct 2001 A1
20020036765 McCaffrey Mar 2002 A1
20020054289 Thibault et al. May 2002 A1
20020067855 Chiu et al. Jun 2002 A1
20020105639 Roelke Aug 2002 A1
20020109835 Goetz Aug 2002 A1
20020113946 Kitaguchi et al. Aug 2002 A1
20020118874 Chung Aug 2002 A1
20020158873 Williamson Oct 2002 A1
20020167677 Okada et al. Nov 2002 A1
20020179708 Zhu et al. Dec 2002 A1
20020196534 Lizotte et al. Dec 2002 A1
20030038179 Tsikos et al. Feb 2003 A1
20030053513 Vatan et al. Mar 2003 A1
20030063086 Baumberg Apr 2003 A1
20030091227 Chang et al. May 2003 A1
20030156756 Gokturk et al. Aug 2003 A1
20030197138 Pease et al. Oct 2003 A1
20030225712 Cooper et al. Dec 2003 A1
20030235331 Kawaike et al. Dec 2003 A1
20040019274 Galloway et al. Jan 2004 A1
20040024754 Mane et al. Feb 2004 A1
20040066329 Leitfuss et al. Apr 2004 A1
20040073359 Ichijo et al. Apr 2004 A1
20040083025 Yamanouchi et al. Apr 2004 A1
20040089482 Ramsden et al. May 2004 A1
20040098146 Katae et al. May 2004 A1
20040105580 Hager et al. Jun 2004 A1
20040118928 Patel et al. Jun 2004 A1
20040122779 Stickler et al. Jun 2004 A1
20040132297 Baba et al. Jul 2004 A1
20040155975 Hart et al. Aug 2004 A1
20040165090 Ning Aug 2004 A1
20040184041 Schopp Sep 2004 A1
20040211836 Patel et al. Oct 2004 A1
20040214623 Takahashi et al. Oct 2004 A1
20040008259 Gokturk et al. Nov 2004 A1
20040233461 Armstrong Nov 2004 A1
20040258353 Gluckstad et al. Dec 2004 A1
20050006477 Patel Jan 2005 A1
20050117215 Lange Jun 2005 A1
20050128193 Popescu et al. Jun 2005 A1
20050128196 Popescu et al. Jun 2005 A1
20050168488 Montague Aug 2005 A1
20050211782 Martin Sep 2005 A1
20050240317 Kienzle-Lietl Oct 2005 A1
20050257748 Kriesel et al. Nov 2005 A1
20050264867 Cho et al. Dec 2005 A1
20060047704 Gopalakrishnan Mar 2006 A1
20060078226 Zhou Apr 2006 A1
20060108266 Bowers et al. May 2006 A1
20060109105 Varner et al. May 2006 A1
20060112023 Horhann May 2006 A1
20060151604 Zhu et al. Jul 2006 A1
20060159307 Anderson et al. Jul 2006 A1
20060159344 Shao et al. Jul 2006 A1
20060232681 Okada Oct 2006 A1
20060255150 Longacre Nov 2006 A1
20060269165 Viswanathan Nov 2006 A1
20060276709 Khamene et al. Dec 2006 A1
20060291719 Ikeda et al. Dec 2006 A1
20070003154 Sun et al. Jan 2007 A1
20070025612 Iwasaki et al. Feb 2007 A1
20070031064 Zhao et al. Feb 2007 A1
20070063048 Havens et al. Mar 2007 A1
20070116357 Dewaele May 2007 A1
20070127022 Cohen et al. Jun 2007 A1
20070143082 Degnan Jun 2007 A1
20070153293 Gruhlke et al. Jul 2007 A1
20070165013 Goulanian et al. Jul 2007 A1
20070171220 Kriveshko Jul 2007 A1
20070177011 Lewin et al. Aug 2007 A1
20070181685 Zhu et al. Aug 2007 A1
20070237356 Dwinell et al. Oct 2007 A1
20070291031 Konev et al. Dec 2007 A1
20070299338 Stevick et al. Dec 2007 A1
20080013793 Hillis et al. Jan 2008 A1
20080035390 Wurz Feb 2008 A1
20080047760 Georgitsis Feb 2008 A1
20080050042 Zhang et al. Feb 2008 A1
20080056536 Hildreth et al. Mar 2008 A1
20080062164 Bassi et al. Mar 2008 A1
20080065509 Williams Mar 2008 A1
20080077265 Boyden Mar 2008 A1
20080079955 Storm Apr 2008 A1
20080164074 Wurz Jun 2008 A1
20080204476 Montague Aug 2008 A1
20080212168 Olmstead et al. Sep 2008 A1
20080247635 Davis et al. Oct 2008 A1
20080273191 Kim et al. Nov 2008 A1
20080273210 Hilde Nov 2008 A1
20080278790 Boesser et al. Nov 2008 A1
20090046296 Kilpartrick et al. Feb 2009 A1
20090059004 Bochicchio Mar 2009 A1
20090095047 Patel et al. Apr 2009 A1
20090114818 Casares et al. May 2009 A1
20090134221 Zhu et al. May 2009 A1
20090161090 Campbell et al. Jun 2009 A1
20090189858 Lev et al. Jul 2009 A1
20090195790 Zhu et al. Aug 2009 A1
20090225333 Bendall et al. Sep 2009 A1
20090237411 Gossweiler et al. Sep 2009 A1
20090268023 Hsieh Oct 2009 A1
20090272724 Gubler Nov 2009 A1
20090273770 Bauhahn et al. Nov 2009 A1
20090313948 Buckley et al. Dec 2009 A1
20090318815 Barnes et al. Dec 2009 A1
20090323084 Dunn et al. Dec 2009 A1
20090323121 Valkenburg Dec 2009 A1
20100035637 Varanasi et al. Feb 2010 A1
20100060604 Zwart et al. Mar 2010 A1
20100091104 Sprigle Apr 2010 A1
20100113153 Yen et al. May 2010 A1
20100118200 Gelman et al. May 2010 A1
20100128109 Banks May 2010 A1
20100161170 Siris Jun 2010 A1
20100171740 Andersen et al. Jul 2010 A1
20100172567 Prokoski Jul 2010 A1
20100177076 Essinger et al. Jul 2010 A1
20100177080 Essinger et al. Jul 2010 A1
20100177707 Essinger et al. Jul 2010 A1
20100177749 Essinger et al. Jul 2010 A1
20100202702 Benos Aug 2010 A1
20100208039 Stettner Aug 2010 A1
20100211355 Horst et al. Aug 2010 A1
20100217678 Goncalves Aug 2010 A1
20100220849 Colbert et al. Sep 2010 A1
20100220894 Ackley et al. Sep 2010 A1
20100223276 Al-Shameri et al. Sep 2010 A1
20100245850 Lee et al. Sep 2010 A1
20100254611 Amz Oct 2010 A1
20100274728 Kugelman Oct 2010 A1
20100303336 Abraham Dec 2010 A1
20100315413 Izadi et al. Dec 2010 A1
20100321482 Cleveland Dec 2010 A1
20110019155 Daniel et al. Jan 2011 A1
20110040192 Brenner et al. Feb 2011 A1
20110040407 Lim Feb 2011 A1
20110043609 Choi et al. Feb 2011 A1
20110075936 Deaver Mar 2011 A1
20110081044 Peeper Apr 2011 A1
20110099474 Grossman et al. Apr 2011 A1
20110169999 Grunow et al. Jul 2011 A1
20110180695 Li et al. Jul 2011 A1
20110188054 Petronius et al. Aug 2011 A1
20110188741 Sones et al. Aug 2011 A1
20110202554 Powilleit et al. Aug 2011 A1
20110234389 Mellin Sep 2011 A1
20110235854 Berger et al. Sep 2011 A1
20110249864 Venkatesan et al. Oct 2011 A1
20110254840 Halstead Oct 2011 A1
20110260965 Kim et al. Oct 2011 A1
20110279916 Brown et al. Nov 2011 A1
20110286007 Pangrazio et al. Nov 2011 A1
20110286628 Goncalves et al. Nov 2011 A1
20110288818 Thierman Nov 2011 A1
20110297590 Ackley et al. Dec 2011 A1
20110301994 Tieman Dec 2011 A1
20110303748 Lemma et al. Dec 2011 A1
20110310227 Konertz Dec 2011 A1
20120024952 Chen Feb 2012 A1
20120056982 Katz et al. Mar 2012 A1
20120057345 Kuchibhotla Mar 2012 A1
20120067955 Rowe Mar 2012 A1
20120074227 Ferren et al. Mar 2012 A1
20120081714 Pangrazio et al. Apr 2012 A1
20120111946 Golant May 2012 A1
20120113223 Hilliges et al. May 2012 A1
20120126000 Kunzig et al. May 2012 A1
20120140300 Freeman Jun 2012 A1
20120168509 Nunnink et al. Jul 2012 A1
20120168512 Kotlarsky et al. Jul 2012 A1
20120179665 Baarman et al. Jul 2012 A1
20120185094 Rosenstein et al. Jul 2012 A1
20120190386 Anderson Jul 2012 A1
20120193423 Samek Aug 2012 A1
20120197464 Wang et al. Aug 2012 A1
20120201288 Kolze et al. Aug 2012 A1
20120203647 Smith Aug 2012 A1
20120218436 Rodriguez et al. Sep 2012 A1
20120223141 Good et al. Sep 2012 A1
20120224026 Bayer et al. Sep 2012 A1
20120224060 Gurevich et al. Sep 2012 A1
20120236212 Itoh et al. Sep 2012 A1
20120236288 Stanley Sep 2012 A1
20120242852 Hayward et al. Sep 2012 A1
20120113250 Farlotti et al. Oct 2012 A1
20120256901 Bendall Oct 2012 A1
20120262558 Boger et al. Oct 2012 A1
20120280908 Rhoads et al. Nov 2012 A1
20120282905 Owen Nov 2012 A1
20120282911 Davis et al. Nov 2012 A1
20120284012 Rodriguez et al. Nov 2012 A1
20120284122 Brandis Nov 2012 A1
20120284339 Rodriguez Nov 2012 A1
20120284593 Rodriguez Nov 2012 A1
20120293610 Doepke et al. Nov 2012 A1
20120293625 Schneider et al. Nov 2012 A1
20120294549 Doepke Nov 2012 A1
20120299961 Ramkumar et al. Nov 2012 A1
20120300991 Mikio Nov 2012 A1
20120313848 Galor et al. Dec 2012 A1
20120314030 Datta Dec 2012 A1
20120314058 Bendall et al. Dec 2012 A1
20120316820 Nakazato et al. Dec 2012 A1
20130019278 Sun Jan 2013 A1
20130038881 Pesach et al. Feb 2013 A1
20130038941 Pesach et al. Feb 2013 A1
20130043312 Van Horn Feb 2013 A1
20130050426 Sarmast et al. Feb 2013 A1
20130075168 Amundsen et al. Mar 2013 A1
20130076857 Kurashige et al. Mar 2013 A1
20130093895 Palmer et al. Apr 2013 A1
20130094069 Lee et al. Apr 2013 A1
20130101158 Lloyd et al. Apr 2013 A1
20130156267 Muraoka et al. Jun 2013 A1
20130175341 Kearney et al. Jul 2013 A1
20130175343 Good Jul 2013 A1
20130200150 Reynolds et al. Aug 2013 A1
20130208164 Cazier et al. Aug 2013 A1
20130211790 Loveland et al. Aug 2013 A1
20130222592 Gieseke Aug 2013 A1
20130223673 Davis et al. Aug 2013 A1
20130257744 Daghigh et al. Oct 2013 A1
20130257759 Daghigh Oct 2013 A1
20130270346 Xian et al. Oct 2013 A1
20130287258 Kearney Oct 2013 A1
20130291998 Konnerth Nov 2013 A1
20130292475 Kotlarsky et al. Nov 2013 A1
20130292477 Hennick et al. Nov 2013 A1
20130293539 Hunt et al. Nov 2013 A1
20130293540 Laffargue et al. Nov 2013 A1
20130306728 Thuries et al. Nov 2013 A1
20130306731 Pedraro Nov 2013 A1
20130307964 Bremer et al. Nov 2013 A1
20130308013 Li et al. Nov 2013 A1
20130308625 Corcoran Nov 2013 A1
20130313324 Koziol et al. Nov 2013 A1
20130313325 Wilz et al. Nov 2013 A1
20130317642 Asaria Nov 2013 A1
20130329012 Bartos Dec 2013 A1
20130329013 Metois et al. Dec 2013 A1
20130342342 Sabre et al. Dec 2013 A1
20130342717 Havens et al. Dec 2013 A1
20140001267 Giordano et al. Jan 2014 A1
20140002828 Laffargue et al. Jan 2014 A1
20140008439 Wang Jan 2014 A1
20140009586 McNamer et al. Jan 2014 A1
20140019005 Lee et al. Jan 2014 A1
20140021259 Moed et al. Jan 2014 A1
20140025584 Liu et al. Jan 2014 A1
20140031665 Pinto et al. Jan 2014 A1
20140034731 Gao et al. Feb 2014 A1
20140034734 Sauerwein Feb 2014 A1
20140036848 Pease et al. Feb 2014 A1
20140039674 Motoyama et al. Feb 2014 A1
20140039693 Havens et al. Feb 2014 A1
20140042814 Kather et al. Feb 2014 A1
20140049120 Kohtz et al. Feb 2014 A1
20140049635 Laffargue et al. Feb 2014 A1
20140058612 Wong et al. Feb 2014 A1
20140061306 Wu et al. Mar 2014 A1
20140062709 Hyer Mar 2014 A1
20140063289 Hussey et al. Mar 2014 A1
20140066136 Sauerwein et al. Mar 2014 A1
20140067104 Osterhout Mar 2014 A1
20140067692 Ye et al. Mar 2014 A1
20140070005 Nahill et al. Mar 2014 A1
20140071430 Hansen et al. Mar 2014 A1
20140071840 Venancio Mar 2014 A1
20140074746 Wang Mar 2014 A1
20140076974 Havens et al. Mar 2014 A1
20140078341 Havens et al. Mar 2014 A1
20140078342 Li et al. Mar 2014 A1
20140078345 Showering Mar 2014 A1
20140079297 Tadayon et al. Mar 2014 A1
20140091147 Evans et al. Apr 2014 A1
20140097238 Ghazizadeh Apr 2014 A1
20140097252 He et al. Apr 2014 A1
20140098091 Hori Apr 2014 A1
20140098243 Ghazizadeh Apr 2014 A1
20140098792 Wang et al. Apr 2014 A1
20140100774 Showering Apr 2014 A1
20140100813 Showering Apr 2014 A1
20140103115 Meier et al. Apr 2014 A1
20140104413 McCloskey et al. Apr 2014 A1
20140104414 McCloskey et al. Apr 2014 A1
20140104416 Li et al. Apr 2014 A1
20140104451 Todeschini et al. Apr 2014 A1
20140104664 Lee Apr 2014 A1
20140106594 Skvoretz Apr 2014 A1
20140106725 Sauerwein Apr 2014 A1
20140108010 Maltseff et al. Apr 2014 A1
20140108402 Gomez et al. Apr 2014 A1
20140108682 Caballero Apr 2014 A1
20140110485 Toa et al. Apr 2014 A1
20140114530 Fitch et al. Apr 2014 A1
20140121438 Kearney May 2014 A1
20140121445 Ding et al. May 2014 A1
20140124577 Wang et al. May 2014 A1
20140124579 Ding May 2014 A1
20140125842 Winegar May 2014 A1
20140125853 Wang May 2014 A1
20140125999 Longacre et al. May 2014 A1
20140129378 Richardson May 2014 A1
20140131441 Nahill et al. May 2014 A1
20140131443 Smith May 2014 A1
20140131444 Wang May 2014 A1
20140131448 Xian et al. May 2014 A1
20140133379 Wang et al. May 2014 A1
20140135984 Hirata May 2014 A1
20140136208 Maltseff et al. May 2014 A1
20140139654 Taskahashi May 2014 A1
20140140585 Wang May 2014 A1
20140142398 Patil et al. May 2014 A1
20140151453 Meier et al. Jun 2014 A1
20140152882 Samek et al. Jun 2014 A1
20140152975 Ko Jun 2014 A1
20140158468 Adami Jun 2014 A1
20140158770 Sevier et al. Jun 2014 A1
20140159869 Zumsteg et al. Jun 2014 A1
20140166755 Liu et al. Jun 2014 A1
20140166757 Smith Jun 2014 A1
20140166759 Liu et al. Jun 2014 A1
20140168380 Heidemann et al. Jun 2014 A1
20140168787 Wang et al. Jun 2014 A1
20140175165 Havens et al. Jun 2014 A1
20140175172 Jovanovski et al. Jun 2014 A1
20140177931 Kocherscheidt et al. Jun 2014 A1
20140191644 Chaney Jul 2014 A1
20140191913 Ge et al. Jul 2014 A1
20140192187 Atwell et al. Jul 2014 A1
20140192551 Masaki Jul 2014 A1
20140197238 Lui et al. Jul 2014 A1
20140197239 Havens et al. Jul 2014 A1
20140197304 Feng et al. Jul 2014 A1
20140201126 Zadeh et al. Jul 2014 A1
20140203087 Smith et al. Jul 2014 A1
20140204268 Grunow et al. Jul 2014 A1
20140205150 Ogawa Jul 2014 A1
20140214631 Hansen Jul 2014 A1
20140217166 Berthiaume et al. Aug 2014 A1
20140217180 Liu Aug 2014 A1
20140225918 Mittal et al. Aug 2014 A1
20140225985 Klusza et al. Aug 2014 A1
20140231500 Ehrhart et al. Aug 2014 A1
20140232930 Anderson Aug 2014 A1
20140240454 Lee Aug 2014 A1
20140247279 Nicholas et al. Sep 2014 A1
20140247280 Nicholas et al. Sep 2014 A1
20140247315 Marty et al. Sep 2014 A1
20140263493 Amurgis et al. Sep 2014 A1
20140263645 Smith et al. Sep 2014 A1
20140267609 Laffargue Sep 2014 A1
20140268093 Tohme et al. Sep 2014 A1
20140270196 Braho et al. Sep 2014 A1
20140270229 Braho Sep 2014 A1
20140270361 Amma et al. Sep 2014 A1
20140278387 DiGregorio Sep 2014 A1
20140282210 Bianconi Sep 2014 A1
20140284384 Lu et al. Sep 2014 A1
20140288933 Braho et al. Sep 2014 A1
20140297058 Barker et al. Oct 2014 A1
20140299665 Barber et al. Oct 2014 A1
20140306833 Ricci Oct 2014 A1
20140307855 Withagen et al. Oct 2014 A1
20140312121 Lu et al. Oct 2014 A1
20140313527 Askan Oct 2014 A1
20140319219 Liu et al. Oct 2014 A1
20140319220 Coyle Oct 2014 A1
20140319221 Oberpriller et al. Oct 2014 A1
20140320408 Zagorsek et al. Oct 2014 A1
20140326787 Barten Nov 2014 A1
20140332590 Wang et al. Nov 2014 A1
20140344943 Todeschini et al. Nov 2014 A1
20140346233 Liu et al. Nov 2014 A1
20140347533 Ovsiannikov et al. Nov 2014 A1
20140350710 Gopalkrishnan et al. Nov 2014 A1
20140351317 Smith et al. Nov 2014 A1
20140353373 Van Horn et al. Dec 2014 A1
20140361073 Qu et al. Dec 2014 A1
20140361082 Xian et al. Dec 2014 A1
20140362184 Jovanovski et al. Dec 2014 A1
20140363015 Braho Dec 2014 A1
20140369511 Sheerin et al. Dec 2014 A1
20140374483 Lu Dec 2014 A1
20140374485 Xian et al. Dec 2014 A1
20140379613 Nishitani et al. Dec 2014 A1
20150001301 Ouyang Jan 2015 A1
20150001304 Todeschini Jan 2015 A1
20150003673 Fletcher Jan 2015 A1
20150009100 Haneda et al. Jan 2015 A1
20150009301 Ribnick et al. Jan 2015 A1
20150009338 Laffargue et al. Jan 2015 A1
20150009610 London et al. Jan 2015 A1
20150014416 Kotlarsky et al. Jan 2015 A1
20150021397 Rueblinger et al. Jan 2015 A1
20150028102 Ren et al. Jan 2015 A1
20150028103 Jiang Jan 2015 A1
20150028104 Ma et al. Jan 2015 A1
20150029002 Yeakley et al. Jan 2015 A1
20150032709 Maloy et al. Jan 2015 A1
20150036876 Marrion et al. Feb 2015 A1
20150039309 Braho et al. Feb 2015 A1
20150040378 Saber et al. Feb 2015 A1
20150048168 Fritz et al. Feb 2015 A1
20150049347 Laffargue et al. Feb 2015 A1
20150051992 Smith Feb 2015 A1
20150053766 Havens et al. Feb 2015 A1
20150053768 Wang et al. Feb 2015 A1
20150053769 Thuries et al. Feb 2015 A1
20150062366 Liu et al. Mar 2015 A1
20150062369 Gehring et al. Mar 2015 A1
20150063215 Wang Mar 2015 A1
20150063676 Lloyd et al. Mar 2015 A1
20150069130 Gannon Mar 2015 A1
20150070158 Hayasaka Mar 2015 A1
20150071818 Todeschini Mar 2015 A1
20150083800 Li et al. Mar 2015 A1
20150086114 Todeschini Mar 2015 A1
20150088522 Hendrickson et al. Mar 2015 A1
20150096872 Woodburn Apr 2015 A1
20150099557 Pettinelli et al. Apr 2015 A1
20150100196 Hollifield Apr 2015 A1
20150102109 Huck Apr 2015 A1
20150115035 Meier et al. Apr 2015 A1
20150116498 Vartiainen et al. Apr 2015 A1
20150117749 Chen et al. Apr 2015 A1
20150127791 Kosecki et al. May 2015 A1
20150128116 Chen et al. May 2015 A1
20150129659 Feng et al. May 2015 A1
20150133047 Smith et al. May 2015 A1
20150134470 Hejl et al. May 2015 A1
20150136851 Harding et al. May 2015 A1
20150136854 Lu et al. May 2015 A1
20150142492 Kumar May 2015 A1
20150144692 Hejl May 2015 A1
20150144698 Teng et al. May 2015 A1
20150144701 Xian et al. May 2015 A1
20150149946 Benos et al. May 2015 A1
20150161429 Xian Jun 2015 A1
20150163474 You Jun 2015 A1
20150169925 Chang et al. Jun 2015 A1
20150169929 Williams et al. Jun 2015 A1
20150178900 Kim et al. Jun 2015 A1
20150186703 Chen et al. Jul 2015 A1
20150193644 Kearney et al. Jul 2015 A1
20150193645 Colavito et al. Jul 2015 A1
20150199957 Funyak et al. Jul 2015 A1
20150204662 Kobayashi et al. Jul 2015 A1
20150204671 Showering Jul 2015 A1
20150213647 Laffargue et al. Jul 2015 A1
20150219748 Hyatt Aug 2015 A1
20150229838 Hakim et al. Aug 2015 A1
20150253469 Le Gros et al. Sep 2015 A1
20150260830 Ghosh et al. Sep 2015 A1
20150269403 Lei et al. Sep 2015 A1
20150201181 Herschbach Oct 2015 A1
20150276379 Ni Oct 2015 A1
20150308816 Laffargue et al. Oct 2015 A1
20150316368 Moench et al. Nov 2015 A1
20150325036 Lee Nov 2015 A1
20150332463 Galera et al. Nov 2015 A1
20150355470 Herschbach Dec 2015 A1
20160169665 Deschenes et al. Jan 2016 A1
20160048725 Holz et al. Feb 2016 A1
20160063429 Varley et al. Mar 2016 A1
20160065912 Peterson Mar 2016 A1
20160090283 Svensson et al. Mar 2016 A1
20160090284 Svensson et al. Mar 2016 A1
20160094016 Beach et al. Mar 2016 A1
20160138247 Conway et al. May 2016 A1
20160138248 Conway et al. May 2016 A1
20160138249 Svensson et al. May 2016 A1
20160164261 Warren Jun 2016 A1
20160178915 Mor et al. Jun 2016 A1
20160187186 Coleman et al. Jun 2016 A1
20160187187 Coleman et al. Jun 2016 A1
20160187210 Coleman et al. Jun 2016 A1
20160191801 Sivan Jun 2016 A1
20160202478 Masson et al. Jul 2016 A1
20160203641 Bostick et al. Jul 2016 A1
20160223474 Tang et al. Aug 2016 A1
20170115490 Hsieh et al. Apr 2017 A1
20170115497 Chen et al. Apr 2017 A1
20170121158 Wong May 2017 A1
20170139213 Schmidtlin May 2017 A1
20107018294 Hardy et al. Jun 2017
20170309108 Sadovsky et al. Oct 2017 A1
20170336870 Everett et al. Nov 2017 A1
Foreign Referenced Citations (61)
Number Date Country
2004212587 Apr 2005 AU
201139117 Oct 2008 CN
3335760 Apr 1985 DE
10210813 Oct 2003 DE
102007037282 Mar 2008 DE
3007096 Apr 2016 EE
1111435 Jun 2001 EP
1443312 Aug 2004 EP
1112483 May 2006 EP
1232480 May 2006 EP
2013117 Jan 2009 EP
2286932 Feb 2011 EP
2372648 Oct 2011 EP
2381421 Oct 2011 EP
2533009 Dec 2012 EP
2562715 Feb 2013 EP
2722656 Apr 2014 EP
2779027 Sep 2014 EP
2833323 Feb 2015 EP
2843590 Mar 2015 EP
2843590 Mar 2015 EP
2845170 Mar 2015 EP
2966595 Jan 2016 EP
3006893 Apr 2016 EP
3012601 Apr 2016 EP
2503978 Jan 2014 GB
2525053 Oct 2015 GB
2531928 May 2016 GB
H04129902 Apr 1992 JP
200696457 Apr 2006 JP
2007084162 Apr 2007 JP
2008210276 Sep 2008 JP
2014210646 Nov 2014 JP
2015174705 Oct 2015 JP
20100020115 Feb 2010 KR
20110013200 Feb 2011 KR
20110117020 Oct 2011 KR
20120028109 Mar 2012 KR
9640452 Dec 1996 WO
0077726 Dec 2000 WO
0114836 Mar 2001 WO
2006095110 Sep 2006 WO
2007015059 Feb 2007 WO
200712554 Nov 2007 WO
2011017241 Feb 2011 WO
2012175731 Dec 2012 WO
2013021157 Feb 2013 WO
2013033442 Mar 2013 WO
2013163789 Nov 2013 WO
2013166368 Nov 2013 WO
2013173985 Nov 2013 WO
20130184340 Dec 2013 WO
2014019130 Feb 2014 WO
2014102341 Jul 2014 WO
2014110495 Jul 2014 WO
2014149702 Sep 2014 WO
2014151746 Sep 2014 WO
2015006865 Jan 2015 WO
2016020038 Feb 2016 WO
2016061699 Apr 2016 WO
2016061699 Apr 2016 WO
Non-Patent Literature Citations (200)
Entry
U.S. Appl. No. 14/519,179 for Dimensioning System With Multipath Interference Mitigation filed Oct. 21, 2014 (Thuries et al.); 30 pages.
U.S. Appl. No. 14/264,173 for Autofocus Lens System for Indicia Readers filed Apr. 29, 2014, (Ackley et al.); 39 pages.
U.S. Appl. No. 14/453,019 for Dimensioning System With Guided Alignment, filed Aug. 6, 2014 (Li et al.); 31 pages.
U.S. Appl. No. 14/452,697 for Interactive Indicia Reader , filed Aug. 6, 2014, (Todeschini); 32 pages.
U.S. Appl. No. 14/231,898 for Hand-Mounted Indicia-Reading Device with Finger Motion Triggering filed Apr. 1, 2014 (Van Horn et al.); 36 pages.
U.S. Appl. No. 14/715,916 for Evaluating Image Values filed May 19, 2015 (Ackley); 60 pages.
U.S. Appl. No. 14/513,808 for Identifying Inventory Items in a Storage Facility filed Oct. 14, 2014 (Singel et al.); 51 pages.
U.S. Appl. No. 29/458,405 for an Electronic Device, filed Jun. 19, 2013 (Fitch et al.); 22 pages.
U.S. Appl. No. 29/459,620 for an Electronic Device Enclosure, filed Jul. 2, 2013 (London et al.); 21 pages.
U.S. Appl. No. 14/483,056 for Variable Depth of Field Barcode Scanner filed Sep. 10, 2014 (McCloskey et al.); 29 pages.
U.S. Appl. No. 14/531,154 for Directing an Inspector Through an Inspection filed Nov. 3, 2014 (Miller et al.); 53 pages.
U.S. Appl. No. 29/525,068 for Tablet Computer With Removable Scanning Device filed Apr. 27, 2015 (Schulte et al.); 19 pages.
U.S. Appl. No. 29/468,118 for an Electronic Device Case, filed Sep. 26, 2013 (Oberpriller et al.); 44 pages.
U.S. Appl. No. 14/340,627 for an Axially Reinforced Flexible Scan Element, filed Jul. 25, 2014 (Reublinger et al.); 41 pages.
U.S. Appl. No. 14/676,327 for Device Management Proxy for Secure Devices filed Apr. 1, 2015 (Yeakley et al.); 50 pages.
U.S. Appl. No. 14/257,364 for Docking System and Method Using Near Field Communication filed Apr. 21, 2014 (Showering); 31 pages.
U.S. Appl. No. 14/327,827 for a Mobile-Phone Adapter for Electronic Transactions, filed Jul. 10, 2014 (Hejl); 25 pages.
U.S. Appl. No. 14/334,934 for a System and Method for Indicia Verification, filed Jul. 18, 2014 (Hejl); 38 pages.
U.S. Appl. No. 29/530,600 for Cyclone filed Jun. 18, 2015 (Vargo et al); 16 pages.
U.S. Appl. No. 14/707,123 for Application Independent DEX/UCS Interface filed May 8, 2015 (Pape); 47 pages.
U.S. Appl. No. 14/283,282 for Terminal Having Illumination and Focus Control filed May 21, 2014 (Liu et al.); 31 pages.
U.S. Appl. No. 14/619,093 for Methods for Training a Speech Recognition System filed Feb. 11, 2015 (Pecorari); 35 pages.
U.S. Appl. No. 29/524,186 for Scanner filed Apr. 17, 2015 (Zhou et al.); 17 pages.
U.S. Appl. No. 14/705,407 for Method and System to Protect Software-Based Network-Connected Devices From Advanced Persistent Threat filed May 6, 2015 (Hussey et al.); 42 pages.
U.S. Appl. No. 14/614,706 for Device for Supporting an Electronic Tool on a User's Hand filed Feb. 5, 2015 (Oberpriller et al.); 33 pages.
U.S. Appl. No. 14/628,708 for Device, System, and Method for Determining the Status of Checkout Lanes filed Feb. 23, 2015 (Todeschini); 37 pages.
U.S. Appl. No. 14/704,050 for Intermediate Linear Positioning filed May 5, 2015 (Charpentier et al.); 60 pages.
U.S. Appl. No. 14/529,563 for Adaptable Interface for a Mobile Computing Device filed Oct. 31, 2014 (Schoon et al.); 36 pages.
U.S. Appl. No. 14/705,012 for Hands-Free Human Machine Interface Responsive to a Driver of a Vehicle filed May 6, 2015 (Fitch et al.); 44 pages.
U.S. Appl. No. 14/715,672 for Augumented Reality Enabled Hazard Display filed May 19, 2015 (Venkatesha et al.); 35 pages.
U.S. Appl. No. 14/695,364 for Medication Management System filed Apr. 24, 2015 (Sewell et al.); 44 pages.
U.S. Appl. No. 14/664,063 for Method and Application for Scanning a Barcode With a Smart Device While Continuously Running and Displaying an Application on the Smart Device Display filed Mar. 20, 2015 (Todeschini); 37 pages.
U.S. Appl. No. 14/735,717 for Indicia-Reading Systems Having an Interface With a User's Nervous System filed Jun. 10, 2015 (Todeschini); 39 pages.
U.S. Appl. No. 14/527,191 for Method and System for Recognizing Speech Using Wildcards in an Expected Response filed Oct. 29, 2014 (Braho et al.); 45 pages.
U.S. Appl. No. 14/702,110 for System and Method for Regulating Barcode Data Injection Into a Running Application on a Smart Device filed May 1, 2015 (Todeschini et al.); 38 pages.
U.S. Appl. No. 14/535,764 for Concatenated Expected Responses for Speech Recognition filed Nov. 7, 2014 (Braho et al.); 51 pages.
U.S. Appl. No. 14/687,289 for System for Communication via a Peripheral Hub filed Apr. 15, 2015 (Kohtz et al.); 37 pages.
U.S. Appl. No. 14/747,197 for Optical Pattern Projector filed Jun. 23, 2015 (Thuries et al.); 33 pages.
U.S. Appl. No. 14/674,329 for Aimer for Barcode Scanning filed Mar. 31, 2015 (Bidwell); 36 pages.
U.S. Appl. No. 14/702,979 for Tracking Battery Conditions filed May 4, 2015 (Young et al.); 70 pages.
U.S. Appl. No. 29/529,441 for Indicia Reading Device filed Jun. 8, 2015 (Zhou et al.); 14 pages.
U.S. Appl. No. 14/747,490 for Dual-Projector Three-Dimensional Scanner filed Jun. 23, 2015 (Jovanovski et al.); 40 pages.
U.S. Appl. No. 14/740,320 for Tactile Switch for a Mobile Electronic Device filed Jun. 16, 2015 (Barndringa); 38 pages.
U.S. Appl. No. 14/695,923 for Secure Unattended Network Authentication filed Apr. 24, 2015 (Kubler et al.); 52 pages.
U.S. Appl. No. 14/740,373 for Calibrating a Volume Dimensioner filed Jun. 16, 2015 (Ackley et al.); 63 pages.
U.S. Appl. No. 14/800,757 , Eric Todeschini, filed Jul. 16, 2015, not published yet, Dimensioning and Imaging Items, 80 pages.
Proesmans, Marc et al. “Active Acquisition of 3D Shape for Moving Objects” 0-7803-3258-X/96 1996 IEEE; 4 pages.
U.S. Appl. No. 14/747,197, Serge Thuries et al., filed Jun. 23, 2015, not published yet, Optical Pattern Projector; 33 pages.
U.S. Appl. No. 14/747,490, Brian L Jovanovski et al., filed Jun. 23, 2015, not published yet, Dual-Projector Three-Dimensional Scanner; 40 pages.
U.S. Appl. No. 14/715,916, H. Sprague Ackley, filed May 19, 2015, not published yet, Evaluating Image Values; 54 pages.
U.S. Appl. No. 14/793,149, H. Sprague Ackley, filed Jul. 7, 2015, not published yet, Mobile Dimensioner Apparatus for Use in Commerce; 57 pages.
U.S. Appl. No. 14/740,373, H. Sprague Ackley et al., filed Jun. 16, 2015, not published yet, Calibrating a Volume Dimensioner; 63 pages.
U.S. Appl. No. 14/801,023, Tyler Doomenbal et al., filed Jul. 16, 2015, not published yet, Adjusting Dimensioning Results Using Augmented Reality, 39 pages.
Leotta, Matthew, Generic, Deformable Models for 3-D Vehicle Surveillance, May 2010, Doctoral Dissertation, Brown University, Providence RI, 248 pages.
Ward, Benjamin, Interactive 3D Reconstruction from Video, Aug. 2012, Doctoral Thesis, Univesity of Adelaide, Adelaide, South Australia, 157 pages.
Hood, Frederick W.; William A. Hoff, Robert King, Evaluation of an Interactive Technique for Creating Site Models from Range Data, Apr. 27-May 1, 1997 Proceedings of the ANS 7th Topical Meeting on Robotics & Remote Systems, Augusta GA, 9 pages.
Gupta, Alok; Range Image Segmentation for 3-D Objects Recognition, May 1988, Technical Reports (CIS), Paper 736, University of Pennsylvania Department of Computer and Information Science, retrieved from Http://repository.upenn.edu/cis_reports/736, Accessed May 31, 2015, 157 pages.
Reisner-Kollmann,Irene; Anton L Fuhrmann, Werner Purgathofer, Interactive Reconstruction of Industrial Sites Using Parametric Models, May 2010, Proceedings of the 26th Spring Conference of Computer Graphics SCCG 10, 8 pages.
Drummond, Tom; Roberto Cipolla, Real-Time Visual Tracking of Complex Structures, Jul. 2002, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, No. 7; 15 pages.
Zhang, Zhaoxiang; Tieniu Tan, Kaiqi Huang, Yunhong Wang; Three-Dimensional Deformable-Model-based Localization and Recognition of Road Vehicles; IEEE Transactions on Image Processing, vol. 21, No. 1, Jan. 2012, 13 pages.
Leotta, Matthew J.; Joseph L. Mundy; Predicting High Resolution Image Edges with a Generic, Adaptive, 3-D Vehicle Model; IEEE Conference on Computer Vision and Pattern Recognition, 2009; 8 pages.
Spiller, Jonathan; Object Localization Using Deformable Templates, Master's Dissertation, University of the Witwatersrand, Johannesburg, South Africa, 2007; 74 pages.
EP Search and Written Opinion Report in related matter EP Application No. 14181437.6, dated Mar. 26, 2015, 7 pages.
Hetzel, Gunter et al.; “3D Object Recognition from Range Images using Local Feature Histograms,”, Proceedings 2001 IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2001. Kauai, Hawaii, Dec. 8-14, 2001; pp. 394-399, XP010584149, ISBN: 978-0-7695-1272-3.
Intention to Grant in counterpart European Application No. 14157971.4 dated Apr. 14, 2015, pp. 1-8.
Decision to Grant in counterpart European Application No. 14157971.4 dated Aug. 6, 2015, pp. 1-2.
Salvi, Joaquim et al. “Pattern Codification Strategies in Structured Light Systems” published in Pattern Recognition; The Journal of the Pattern Recognition Society, Received Mar. 6, 2003; Accepted Oct. 2, 2003; 23 pages.
Office Action in counterpart European Application No. 13186043.9 dated Sep. 30, 2015, pp. 1-7.
Lloyd et al., “System for Monitoring the Condition of Packages Throughout Transit”, U.S. Appl. No. 14/865,575, filed Sep. 25, 2015, 59 pages, not yet published.
James Chamberlin, “System and Method for Picking Validation”, U.S. Appl. No. 14/865,797, filed Sep. 25, 2015, 44 pages, not yet published.
Jovanovski et al., “Image-Stitching for Dimensioning”, U.S. Appl. No. 14/870,488, filed Sep. 30, 2015, 45 pages, not yet published.
Todeschini et al.; “Depth Sensor Based Auto-Focus System for an Indicia Scanner,” U.S. Appl. No. 14/872,176, filed Oct. 1, 2015, 44 pages, not yet published.
Wikipedia, “3D projection” Downloaded on Nov. 25, 2015 from www.wikipedia.com, 4 pages.
McCloskey et al., “Methods for Improving the Accuracy of Dimensioning-System Measurements,” U.S. Appl. No. 14/873,613, filed Sep. 2, 2015, 47 pages, not yet published.
Search Report in counterpart European Application No. 15182675.7, dated Dec. 4, 2015, 10 pages.
McCloskey et al., “Image Transformation for Indicia Reading,” U.S. Appl. No. 14/982,032, filed Oct. 30, 2015, 48 pages, not yet published.
Search Report and Opinion in related GB Application No. 1517112.7, dated Feb. 19, 2016, 6 Pages (GB2503978 is a commonly owned now abandoned application and not cited above).
Lloyd, Ryan and Scott McCloskey, “Recognition of 3D Package Shapes for Singe Camera Metrology” IEEE Winter conference on Applications of computer Visiona, IEEE, Mar. 24, 2014, pp. 99-106, {retrieved on Jun. 16, 2014}, Authors are employees of common Applicant.
European Search Report for Related EP Application No. 15189214.8, dated Mar. 3, 2016, 9 pages.
European Partial Search Report for related EP Application No. 15190306.9, dated May 6, 2016, 8 pages.
Mike Stensvold, “Get the Most Out of Variable Aperture Lenses”, published on www.OutdoorPhotogrpaher.com; dated Dec. 7, 2010; 4 pages, [As noted on search report retrieved from URL: http;//www.outdoorphotographer.com/gear/lenses/get-the-most-out-ofvariable-aperture-lenses.html on Feb. 9, 2016].
European Search Report for related EP Application No. 16152477.2, dated May 24, 2016, 8 pages [New Reference cited herein; Reference DE102007037282 A1 and its US Counterparts have been previously cited.].
Second Chinese Office Action in related CN Application No. 201520810685.6, dated Mar. 22, 2016, 5 pages, no references.
European Search Report in related EP Application No. 15190315.0, dated Apr. 1, 2016, 7 pages [Commonly owned Reference 2014/0104416 has been previously cited].
Second Chinese Office Action in related CN Application No. 2015220810562.2, dated Mar. 22, 2016, 5 pages. English Translation provided [No references].
European Search Report for related Application EP 15190249.1, dated Mar. 22, 2016, 7 pages.
Second Chinese Office Action in related CN Application No. 201520810313.3, dated Mar. 22, 2016, 5 pages. English Translation provided [No references].
Search Report and Opinion in Related EP Application 15176943.7, dated Jan. 8, 2016, 8 pages, (US Application 2014/0049635 has been previously cited).
European Search Report for related EP Application No. 15188440.0, dated Mar. 8, 2016, 8 pages.
United Kingdom Search Report in related application GB1517842.9, dated Apr. 8, 2016, 8 pages.
Great Britain Search Report for related Application On. GB1517843.7, dated Feb. 23, 2016; 8 pages.
M.Zahid Gurbuz, Selim Akyokus, Ibrahim Emiroglu, Aysun Guran, An Efficient Algorithm for 3D Rectangular Box Jacking, 2009, Applied Automatic Systems: Proceedings of Selected AAS 2009 Papers, pp. 131-134 [Examiner cited art in related US matter with Notice of Allowance dated Aug. 11, 2016].
U.S. Appl. No. 15/182,636; H. Sprague Ackley et al., Automatic Mode Switching In a Volumer Dimensioner, not yet published, filed Jun. 15, 2016, 53 pages.
European Extended search report in related EP Application No. 15190306.9, dated Sep. 9, 2016, 15 pages [only new references are cited; remaining references were cited with partial search report in same application dated May 6, 2016].
Collings et al., “The Applications and Technology of Phase-Only Liquid Crystal on Silicon Devices”, Journal of Display Technology, IEEE Service Center, New, York, NY, US, vol. 7, No. 3, Mar. 1, 2011 (Mar. 1, 2011), pp. 112-119.
European extended Search report in related EP Application 13785171.3, dated Sep. 19, 2016, 8 pages.
El-Hakim et al., “Multicamera vision-based approach to flexible feature measurement for inspection and reverse engineering”, published in Optical Engineering, Society of Photo-Optical Instrumentation Engineers, vol. 32, No. 9, Sep. 1, 1993, 15 pages.
El-Hakim et al., “A Knowledge-based Edge/Object Measurement Technique”, Retrieved from the Internet: URL: https://www.researchgate.net/profile/Sabry_E1-Hakim/publication/44075058_A_Knowledge_Based_EdgeObject_Measurement_Technique/links/00b4953b5faa7d3304000000.pdf [retrieved on Jul. 15, 2016] dated Jan. 1, 1993, 9 pages.
United Kingdom combined Search and Examination Report in related GB Application No. 1607394.2, dated Oct. 19, 2016, 7 pages.
European Extended Search Report in Related EP Application No. 16172995.9, dated Aug. 22, 2016, 11 pages (Only new references have been cited; U.S. Pat. No. 8,463,079 (formerly U.S. Publication 201010220894) and U.S. Publication 2001/0027955 have been previously cited.).
European Search Report from related EP Application No. 16168216.6, dated Oct. 20, 2016, 8 pages [New reference cited above; U.S. Publication 2014/0104413 has been previously cited].
Peter Clarke, Actuator Develop Claims Anti-Shake Breakthrough for Smartphone Cams, Electronic Engineering Times, p. 24, May 16, 2011.
U.S. Appl. No. 14/055,234, not yet published, Hand Held Products, Inc. filed Oct. 16, 2013; Dimensioning System; 26 pages.
U.S. Appl. No. 13/912,262, not yet published, filed Jun. 7, 2013, Hand Held Products Inc., Method Error Correction for 3D Imaging Device; 33 pages.
European Search Report for application No. EP13186043 dated Feb. 26, 2014 (now EP2722656 (Apr. 23, 2014)): Total pp. 7.
International Search Report for PCT/US2013/039438 (WO2013166368), dated Oct. 1, 2013, 7 pages.
U.S. Appl. No. 14/453,019, not yet published, filed Aug. 6, 2014, Hand Held Products Inc., Dimensioning System With Guided Alignment: 31 pages.
European Office Action for application EP 13186043, dated Jun. 12, 2014(now EP2722656 (Apr. 23, 2014)), Total of 6 pages.
U.S. Appl. No. 14/461,524, not yet published, filed Aug. 18, 2014, Hand Held Products Inc., System and Method for Package Dimensioning: 21 pages.
U.S. Appl. No. 14/801,023, Tyler Doornenbal et al., filed Jul. 16, 2015, not published yet, Adjusting Dimensioning Results Using Augmented Reality, 39 pages.
Wikipedia, YUV description and definition, downloaded from http://www.wikipeida.org/wiki/YUV on Jun. 29, 2012, 10 pages.
YUV Pixel Format, downloaded from http://www.fource.org/yuv.php on Jun. 29, 2012; 13 pages.
YUV to RGB Conversion, downloaded from http://www.fource.org/fccyvrgb.php on Jun. 29, 2012; 5 pages.
Benos et al., “Semi-Automatic Dimensioning with Imager of a Portable Device,” U.S. Appl. No. 61/149,912, filed Feb. 4, 2009 (now expired), 56 pages.
Dimensional Weight—Wikipedia, The Free Encyclopedia, URL=http://en.wikipedia.org/wiki/Dimensional_weight, download date Aug. 1, 2008, 2 pages.
Dimensioning—Wikipedia, the Free Encyclopedia, URL=http://en.wikipedia.org/wiki/Dimensioning, download date Aug. 1, 2008, 1 page.
European Patent Office Action for Application No. 14157971.4-1906, dated Jul. 16, 2014, 5 pages.
European Patent Search Report for Application No. 14157971.4-1906, dated Jun. 30, 2014, 6 pages.
Caulier, Yannick et al., “A New Type of Color-Coded Light Structures for an Adapted and Rapid Determination of Point Correspondences for 3D Reconstruction.” Proc. of SPIE, vol. 8082 808232-3; 2011; 8 pages.
Kazantsev, Aleksei et al. “Robust Pseudo-Random Coded Colored STructured Light Techniques for 3D Object Model Recovery”; ROSE 2008 IEEE International Workshop on Robotic and Sensors Environments (Oct. 17-18, 2008) , 6 pages.
Mouaddib E. et al. “Recent Progress in Structured Light in order to Solve the Correspondence Problem in Stereo Vision” Proceedings of the 1997 IEEE International Conference on Robotics and Automation, Apr. 1997; 7 pages.
Proesmans, Marc et al. “Active Acquisition of 3D Shape for Moving Objects” 0/7803-3258-X196 1996 IEEE; 4 pages.
Hetzel, Gunter et al.; “3D Object Recognition from Range Images using Local Feature Histograms,”, Proceedings 2OO1 IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2001. Kauai, Hawaii, Dec. 8-14, 2001; pp. 394-399, XP010584149, ISBN: 978-0-7695-1272-3.
U.S. Appl. No. 14/519,179, Serge Thuries et al., filed Oct. 21, 2014, not published yet. Dimensioning System With Multipath Interference Mitigation; 40 pages.
U.S. Appl. No. 14/519,249, H. Sprague Ackley et al., filed Oct. 21, 2014, not published yet. Handheld Dimensioning System With Measurement-Conformance Feedback; 36 pages.
U.S. Appl. No. 14/519,233, Franck Laffargue et al., filed Oct. 21, 2014, not published yet. Handheld Dimensioner With Data-Quality Indication; 34 pages.
U.S. Appl. No. 14/519,211, H. Sprague Ackley et al., filed Oct. 21, 2014, System and Method for Dimensioning; not published yet. 33 pages.
U.S. Appl. No. 14/519,195, Franck Laffargue et al., filed Oct. 21, 2014, not published yet. Handheld Dimensioning System With Feedback; 35 pages.
U.S. Appl. No. 14/795,332, Frankc Laffargue et al., filed Jul. 9, 2015, not published yet, Systems and Methods for Enhancing Dimensioning; 55 pages.
U.S. Appl. No. 13/367,978, filed Feb. 7, 2012, (Feng et al.); now abandoned.
U.S. Appl. No. 14/462,801 for Mobile Computing Device With Data Cognition Software, filed Aug. 19, 2014 (Todeschini et al.); 38 pages.
U.S. Appl. No. 14/596,757 for System and Method for Detecting Barcode Printing Errors filed Jan. 14, 2015 (Ackley); 41 pages.
U.S. Appl. No. 14/277,337 for Multipurpose Optical Reader, filed May 14, 2014 (Jovanovski et al.); 59 pages.
U.S. Appl. No. 14/200,405 for Indicia Reader for Size-Limited Applications filed Mar. 7, 2014 (Feng et al.); 42 pages.
U.S. Appl. No. 14/662,922 for Multifunction Point of Sale System filed Mar. 19, 2015 (Van Horn et al.); 41 pages.
U.S. Appl. No. 14/446,391 for Multifunction Point of Sale Apparatus With Optical Signature Capture filed Jul. 30, 2014 (Good et al.); 37 pages.
U.S. Appl. No. 29/528,165 for In-Counter Barcode Scanner filed May 27, 2015 (Oberpriller et al.); 13 pages.
U.S. Appl. No. 29/528,890 for Mobile Computer Housing filed Jun. 2, 2015 (Fitch et al.); 61 pages.
U.S. Appl. No. 14/614,796 for Cargo Apportionment Techniques filed Feb. 5, 2015 (Morton et al.); 56 pages.
U.S. Appl. No. 29/516,892 for Table Computer filed Feb. 6, 2015 (Bidwell et al.); 13 pages.
U.S. Appl. No. 29/523,098 for Handle for a Tablet Computer filed Apr. 7, 2015 (Bidwell et al.); 17 pages.
U.S. Appl. No. 14/578,627 for Safety System and Method filed Dec. 22, 2014 (Ackley et al.); 32 pages.
U.S. Appl. No. 14/573,022 for Dynamic Diagnostic Indicator Generation filed Dec. 17, 2014 (Goldsmith); 43 pages.
U.S. Appl. No. 14/529,857 for Barcode Reader With Security Features filed Oct. 31, 2014 (Todeschini et al.); 32 pages.
U.S. Appl. No. 14/519,195 for Handheld Dimensioning System With Feedback filed Oct. 21, 2014 (Laffargue et al.); 39 pages.
U.S. Appl. No. 14/519,211 for System and Method for Dimensioning filed Oct. 21, 2014 (Ackley et al.); 33 pages.
U.S. Appl. No. 14/519,233 for Handheld Dimensioner With Data-Quality Indication filed Oct. 21, 2014 (Laffargue et al.); 36 pages.
U.S. Appl. No. 14/533,319 for Barcode Scanning System Using Wearable Device With Embedded Camera filed Nov. 5, 2014 (Todeschini); 29 pages.
U.S. Appl. No. 14/748,446 for Cordless Indicia Reader With a Multifunction Coil for Wireless Charging and EAS Deactivation, filed Jun. 24, 2015 (Xie et al.); 34 pages.
U.S. Appl. No. 29/528,590 for Electronic Device filed May 29, 2015 (Fitch et al.); 9 pages.
U.S. Appl. No. 14/519,249 for Handheld Dimensioning System With Measurement-Conformance Feedback filed Oct. 21, 2014 (Ackley et al.); 36 pages.
U.S. Appl. No. 29/519,017 for Scanner filed Mar. 2, 2015 (Zhou et al.); 11 pages.
U.S. Appl. No. 14/398,542 for Portable Electronic Devices Having a Separate Location Trigger Unit for Use in Controlling an Application Unit filed Nov. 3, 2014 (Bian et al.); 22 pages.
U.S. Appl. No. 14/405,278 for Design Pattern for Secure Store filed Mar. 9, 2015 (Zhu et al.); 23 pages.
U.S. Appl. No. 14/590,024 for Shelving and Package Locating Systems for Delivery Vehicles filed Jan. 6, 2015 (Payne); 31 pages.
U.S. Appl. No. 14/568,305 for Auto-Contrast Viewfinder for an Indicia Reader filed Dec. 12, 2014 (Todeschini); 29 pages.
U.S. Appl. No. 29/526,918 for Charging Base filed May 14, 2015 (Fitch et al.); 10 pages.
U.S. Appl. No. 14/580,262 for Media Gate for Thermal Transfer Printers filed Dec. 23, 2014 (Bowles); 36 pages.
Chinese Notice of Reexamination in related Chinese Application 201520810313.3, dated Mar. 14, 2017, English Computer Translation provided, 7 pages [No new art cited].
Extended European search report in related EP Application 16199707.7, dated Apr. 10, 2017, 15 pages.
Ulusoy et al., One-Shot Scanning using De Bruijn Spaced Grids, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops, 7 pages [Cited in EP Extended search report dated Apr. 10, 2017].
European Exam Report in related EP Application No. 15176943.7, dated Apr. 12, 2017, 6 pages [Art previously cited in this matter].
European Exam Report in related EP Application No. 15188440.0, dated Apr. 21, 2017, 4 pages [No new art to cite].
European Examination report in related EP Application No. 14181437.6, dated Feb. 8, 2017, 5 pages [References have been previously cited].
Wikipedia, “Microlens”, Downloaded from https://en.wikipedia.org/wiki/Microlens, pp. 3. {Cited by Examiner in Feb. 9, 2017 Final Office Action in related matter}.
Fukaya et al., “Characteristics of Speckle Random Pattern and Its Applications”, pp. 317-327, Nouv. Rev. Optique, t.6, n.6. (1975) {Cited by Examiner in Feb. 9, 2017 Final Office Action in related matter: downloaded Mar. 2, 17 from http://iopscience.iop.org}.
European extended search report in related EP Application 16190833.0, dated Mar. 9, 2017, 8 pages [only new art has been cited; US Publication 2014/0034731 was previously cited].
United Kingdom Combined Search and Examination Report in related Application No. GB1620676.5, dated Mar. 8, 2017, 6 pages [References have been previously cited; WO2014/151746, WO2012/175731, US 2014/0313527, GB2503978].
European Exam Report in related , EP Application No. 16168216.6, dated Feb. 27, 2017, 5 pages, [References have been previously cited; WO2011/017241 and US 2014/0104413].
European Exam Report in related EP Application No. 16152477.2, dated Jun. 20, 2017, 4 pages [No art to be cited].
European Exam Report in related EP Applciation 16172995.9, dated Jul. 6, 2017, 9 pages [No new art to be cited].
United Kingdom Search Report in related Application No. GB1700338.5, dated Jun. 30, 2017, 5 pages.
European Search Report in related EP Application No. 17175357.7, dated Aug. 17, 2017, pp. 1-7 [No new art to be cited].
Ralph Grabowski, “Smothing 3D Mesh Objects,” New Commands in AutoCAD 2010: Part 11, Examiner Cited art in related matter Non Final Office Action dated May 19, 2017; 6 pages.
Thorlabs, Examiner Cited NPL in Advisory Action dated Apr. 12, 2017 in related commonly owned application, downloaded from https://www.thorlabs.com/newgrouppage9.cfm?objectgroup_id=6430, 4 pages.
EKSMA Optics, Examiner Cited NPL in Advisory Action dated Apr. 12, 2017 in related commonly owned application, downloaded from http://eksmaoptics.com/optical-systems/f-theta-lenses/f-theta-lens-for-1064-nm/, 2 pages.
Sill Optics, Examiner Cited NPL in Advisory Action dated Apr. 12, 2017 in related commonly owned application, http://www.silloptics.de/1/products/sill-encyclopedia/laser-optics/f-theta-lenses/, 4 pages.
European Extended Search Report in related EP Application No. 16190017.0, dated Jan. 4, 2017, 6 pages.
European Extended Search Report in related EP Application No. 16173429.8, dated Dec. 1, 2016, 8 pages [Only new references cited: US 2013/0038881 was previously cited].
Extended European Search Report in related EP Application No. 16175410.0, dated Dec. 13, 2016, 5 pages.
Padzensky, Ron; “Augmera; Gesture Control”, Dated Apr. 18, 2015, 15 pages [in Office Action dated Jan. 20, 2017 in related Application.].
Grabowski, Ralph; “New Commands in AutoCADS 2010: Part 11 Smoothing 3D Mesh Objects” Dated 2011, 6 pages, [in Office Action dated Jan. 20, 2017 in related Application.].
Theodoropoulos, Gabriel; “Using Gesture Recognizers to Handle Pinch, Rotate, Pan, Swipe, and Tap Gestures” dated Aug. 25, 2014, 34 pages, [in Office Action dated Jan. 20, 2017 in related Application].
EP Search Report in related EP Application No. 17171844 dated Sep. 18, 2017. 4 pages [Only new art cited herein}.
EP Extended Search Report in related EP Applicaton No. 17174843.7 dated Oct. 17, 2017, 5 pages {Only new art cited herein}.
UK Further Exam Report in related UK Application No. GB1517842.9, dated Sep. 1, 2017, 5 pages (only new art cited herein).
Ulusoy, Ali Osman et al.; “One-Shot Scanning using De Bruijn Spaced Grids”, Brown University; 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops, pp. 1786-1792 [Cited in EPO Search Report dated Dec. 5, 2017}.
Extended European Search report in related EP Application No. 17189496.7 dated Dec. 5, 2017; 9 pages.
Extended European Search report in related EP Application No. 17190323.0 dated Jan. 19, 2018; 6 pages [Only new art cited herein].
Examination Report in related GB Application No. GB1517843.7, dated Jan. 19, 2018, 4 pages [Only new art cited herein].
Examination Report in related EP Application No. 15190315, dated Jan. 26, 2018, 6 pages [Only new art cited herein].
Boavida et al., “Dam monitoring using combined terrestrial imaging systems”, 2009 Civil Engineering Survey De/Jan. 2009, pp. 33-38 {Cited in Notice of Allowance dated Sep. 15, 2017 in related matter}.
European Extended Search Report in related EP Application No. 17201794.9, dated Mar. 16, 2018, 10 pages [Only new art cited herein].
European Extended Search Report in related EP Application 17205030.4, dated Mar. 22, 2018, 8 pages.
European Exam Report in related EP Application 16172995.9, dated Mar. 15, 2018, 7 pages (Only new art cited herein).
United Kingdom Combined Search and Examination Report dated Mar. 21, 2018, 5 pages (Art has been previously cited).
European extended Search Report in related Application No. 17207882.6 dated Apr. 26, 2018, 10 pages.
United Kingdom Further Examination Report in related GB Patent Application No. 1517842.9 dated Jul. 26, 2018; 5 pages [Cited art has been previously cited in this matter].
United Kingdom Further Examination Report in related GB Patent Application No. 1517112.7 dated Jul. 17, 2018; 4 pages [No art cited].
United Kingdom Further Examination Report in related GB Patent Application No. 1620676.5 dated Jul. 17, 2018; 4 pages [No art cited].
Related Publications (1)
Number Date Country
20150149946 A1 May 2015 US
Provisional Applications (1)
Number Date Country
61149912 Feb 2009 US
Continuations (1)
Number Date Country
Parent 12685816 Jan 2010 US
Child 14561367 US