This disclosure generally relates to non-contact systems and methods for determining dimensions and volume of one or more objects.
Dimensioning systems are useful for providing dimensional and volumetric data related to three-dimensional objects disposed within a field of view of the dimensioning system. Such dimensional and volumetric information is useful for example, in providing consumers with accurate shipping rates based on the actual size and volume of the object being shipped. Additionally, the dimensioning system's ability to transmit parcel data immediately to a carrier can assist the carrier in selecting and scheduling appropriately sized vehicles based on measured cargo volume and dimensions. Finally, the ready availability of dimensional and volumetric information for all the objects within a carrier's network assists the carrier in ensuring optimal use of available space in the many different vehicles, containers and/or warehouses used in local, interstate, and international commerce.
A wide variety of computing devices are used within the shipping industry. For example, personal computers used as multi-tasking terminals in small storefront packing and shipping establishments. Also, for example, dedicated self-service shipping kiosks found in many post offices. As a further example, dedicated handheld scanners are frequently used as mobile terminals by many international shipping corporations. The wide variety of form factors found in the shipping industry are quite diverse, yet all rely upon providing accurate information, such as parcel dimensions and volume, to both the user in order to provide accurate shipping rates and to the carrier in order to accurately forecast shipping volumes.
The ability to connect and interface a dimensioning system with a variety of platforms such as one finds within the shipping industry presents many physical and logistical challenges. For example, the image sensor or camera used on many systems to provide a simple two-dimensional visual image must often be calibrated to a dimensioning system sensor that is responsible for providing data useful in dimensioning and determining the volume of three-dimensional objects.
A dimensioning system device selectively couplable to an imaging system device that has at least one imaging system image sensor and at least one imaging system display coupled to present display images acquired by the at least one imaging system image sensor may be summarized as including at least one dimensioning system sensor; at least one dimensioning system non-transitory processor-readable medium; and at least one dimensioning system processor communicatively coupled to the at least one dimensioning system non-transitory computer readable medium, where: in a calibration mode the dimensioning system device: captures a depth map; captures an intensity image; receives imaging system image data display image from the imaging system, the imaging system image data representative of an image captured via the at least one imaging sensor; and determines a number of extrinsic parameters that provide a correspondence between a three-dimensional point in each of the depth map and the intensity image as viewed by the dimensioning system sensor with a same three-dimensional point viewed by the at least one imaging system image sensor of the imaging system device; and in a run-time mode the dimensioning system device: generates a packaging wireframe image to be presented by the at least one imaging system display of the imaging system positioned to encompass an object in a display of the image represented by the imaging system image data concurrently presented with the package wireframe image by the at least one imaging system display as correlated spatially therewith based at least in part on the determined extrinsic parameters.
Responsive to the receipt of at least one input when in run-time mode, the dimensioning system device may further: capture a second depth map; capture a second intensity image; receive a second display image from the imaging system; and determine a number of extrinsic parameters that provide a correspondence between a three-dimensional point in each of the second depth map and the second intensity image as viewed by the dimensioning system sensor with a same three-dimensional point viewed by the at least one imaging system image sensor of the imaging system device.
The dimensioning system device may further include a timer configured to provide an output at one or more intervals; and wherein responsive to the at least one output by the timer, the dimensioning system device may further: capture a second depth map; capture a second intensity image; receive a second display image from the imaging system; and determine a number of extrinsic parameters that provide a correspondence between a three-dimensional point in each of the second depth map and the second intensity image as viewed by the dimensioning system sensor with a same three-dimensional point viewed by the at least one imaging system image sensor of the imaging system device.
The dimensioning system device may further include a depth lighting system to selectively illuminate an area within a field of view of the dimensioning system sensor, and wherein the dimensioning system device may selectively illuminate the area contemporaneous with the capture of the depth map and the capture of the intensity image by the dimensioning system sensor.
The depth lighting system may provide at least one of: a structured light pattern or a modulated light pattern.
The dimensioning system device may further include at least one of: an automatic exposure control system, and wherein the automatic exposure control system may adjust an exposure of at least one of the depth map and the intensity image contemporaneous with the selective illumination of the area within the field of view of the dimensioning system sensor; and an automatic gain control system, and wherein the automatic gain control system may adjust a gain of at least one of the depth map and the intensity image contemporaneous with the selective illumination of the area within the field of view of the dimensioning system sensor.
In response to at least one input when in calibration mode, the dimensioning system device may establish a correspondence between a three-dimensional point in each of the depth map and the intensity image as viewed by the dimensioning system sensor with a same three-dimensional point viewed by the at least one imaging system image sensor of the imaging system device. The at least one imaging system display may include a display device configured to provide input/output capabilities; and wherein the at least one input may be provided via the imaging system display.
A method of operation of a dimensioning system device may be summarized as including detecting via a dimensioning system sensor communicably coupled to a dimensioning system processor, a selective coupling of an imaging system device to the dimensioning system device, the imaging system including at least one imaging system image sensor and at least one imaging system display; capturing by the dimensioning system device a depth map via the dimensioning system sensor; capturing by the dimensioning system device an intensity image via the dimensioning system sensor; receiving by the dimensioning system device imaging system image data, the imaging system image data representing an image captured by the at least one imaging system image sensor; and determining by the dimensioning system device a number of extrinsic parameters that provide a correspondence between a point in the depth map and intensity image as viewed by the dimensioning system sensor with a same point as viewed by the at least one imaging system image sensor of the imaging system device.
The method of operation of a dimensioning system device may further include generating by the dimensioning system processor a packaging wireframe model for presentation by the at least one imaging system display of the imaging system, the packaging wireframe model positioned to encompass an object in the imaging system image data concurrently presented by the at least one imaging system display and spatially correlated therewith based at least in part on the determined extrinsic parameters.
Determining by the dimensioning system processor a number of extrinsic parameters that provide a correspondence between a point in the depth map and intensity image as viewed by the dimensioning system sensor with a same point as viewed by the at least one imaging system image sensor of the imaging system device may include determining by the dimensioning system device a number of points positioned on at least one feature in the depth map and the intensity image; and determining by the dimensioning system device an equal number of respective points similarly positioned on the at least one feature in the imaging system image data. Determining by the dimensioning system device a number of points positioned on at least one feature in the depth map and the intensity image may include determining by the dimensioning system device a minimum of at least eight points positioned on at least one feature in the depth map and the intensity image, the at least one feature including an item other than a calibration target. The imaging system image sensor may include a known back focus value (fc); and wherein determining by the dimensioning system processor a number of extrinsic parameters that provide a correspondence between a point in the depth map and intensity image as viewed by the dimensioning system sensor with a same point as viewed by the at least one imaging system image sensor of the imaging system device may include for each of the minimum of at least eight points: determining by the dimensioning system device a point coordinate location (xi, yi) within the intensity image; determining by the dimensioning system device a point depth (zi) within the depth map for the determined point coordinate location (xi, yi); and determining by the dimensioning system device a respective point coordinate location (xc, yc) within the imaging system image data. Determining by the dimensioning system processor a number of extrinsic parameters that provide a correspondence between a point in the depth map and intensity image as viewed by the dimensioning system sensor with a same point as viewed by the at least one imaging system image sensor of the imaging system device may further include determining via the dimensioning system device all of the components of a three-by-three, nine component, Rotation Matrix (R11-33) and a three element Translation Vector (T0-2) that relate the depth map and intensity image to the imaging system image data using the following equations:
Capturing by the dimensioning system device a depth map via the dimensioning system sensor may include selectively illuminating an area within a first field of view of the dimensioning system sensor with at least one of a structured light pattern or a modulated light pattern. Capturing by the dimensioning system device at least one of the depth map or the intensity image may further include at least one of: autonomously adjusting an exposure of the dimensioning system device contemporaneous with the selective illumination of the area within the first field of view of the dimensioning system sensor with at least one of a structured light pattern or a modulated light pattern; and autonomously adjusting a gain of the dimensioning system device contemporaneous with the selective illumination of the area within the first field of view of the dimensioning system sensor with at least one of a structured light pattern or a modulated light pattern. Determining by the dimensioning system processor a number of extrinsic parameters that provide a correspondence between a point in the depth map and intensity image as viewed by the dimensioning system sensor with a same point as viewed by the at least one imaging system image sensor of the imaging system device may include receiving by the dimensioning system device, an input identifying a point located on at least on feature in the depth map and the intensity image; and receiving by the dimensioning system device, a second input identifying a point similarly located on the at least one feature in the imaging system image data.
A method of calibrating a dimensioning system device upon communicably coupling the dimensioning system device to an imaging system including an imaging system display and an imaging system image sensor may be summarized as including receiving by the dimensioning system device a depth map and an intensity image of a scene provided by a dimensioning system sensor in the dimensioning system device, the depth map and the intensity image including a common plurality of three-dimensional points; receiving by the dimensioning system device an imaging system image data from the imaging system image sensor, the imaging system image data comprising a plurality of visible points, at least a portion of the plurality of visible points corresponding to at least a portion of the plurality of three-dimensional points; determining via the dimensioning system device a number of points positioned on at least one feature appearing in the depth map and intensity image with a same number of points similarly positioned on the at least one feature appearing in the imaging system image data, the at least one feature not including a calibration target; determining by the dimensioning system device a number of extrinsic parameters spatially relating each of the number of points in the depth map and the intensity image with each of the respective, same number of points in the imaging system image data.
The method of calibrating a dimensioning system device upon communicably coupling the dimensioning system device to an imaging system including an imaging system display and an imaging system image sensor may further include identifying, by the dimensioning system device, at least one three-dimensional object in the depth map and the intensity image; generating by the dimensioning system device and based at least in part on the determined number of extrinsic parameters, a packaging wireframe for presentation on the imaging system display, the packaging wireframe substantially encompassing the at least one three-dimensional object; and generating by the dimensioning system device, a composite image signal including the three-dimensional wireframe substantially encompassing an image of the three-dimensional object appearing in the imaging system image data; and displaying the composite image signal on the imaging system display.
The imaging system image sensor may include a back focus value (fc); and wherein determining a number of extrinsic parameters spatially relating each of the number of points in the depth map and the intensity image with each of the respective, same number of points in the imaging system image data may include determining by the dimensioning system device at least eight points located on at least one feature in the depth map and the intensity image; and determining by the dimensioning system device an equal number of respective points similarly located on the at least one feature in the imaging system image data; determining by the dimensioning system device for each of the at least eight points a point coordinate location (xi, yi) within the intensity image; determining by the dimensioning system device for each of the at least eight points a point depth (zi) within the depth map for the determined point coordinate location (xi, yi); and determining by the dimensioning system device a respective point coordinate location for each of the at least eight points (xc, yc) within the imaging system image data. Determining a number of extrinsic parameters spatially relating each of the number of points in the depth map and the intensity image with each of the respective, same number of points in the imaging system image data may include determining via the dimensioning system device all of the components of a three-by-three, nine component, Rotation Matrix (R11-33) and a three element Translation Vector (T0-2) that relate the depth map and intensity image to the imaging system image data using the following equations:
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.
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 sources of electromagnetic energy, operative details concerning image sensors and cameras and detailed architecture and operation of the imaging system 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.
As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” include plural referents unless the content clearly dictates otherwise. It should also be noted that the term “or” is generally employed in its sense including “and/or” unless the content clearly dictates otherwise.
The headings and Abstract of the Disclosure provided herein are for convenience only and do not interpret the scope or meaning of the embodiments.
A dimensioning system can generate and display a packaging wireframe model or a shape overlay on a representation (visual, digital) of three-dimensional object within the field of view of the dimensioning system. Generally, the dimensioning system can include one or more sensors that are individually or jointly capable of acquiring at least three-dimensional depth data corresponding to a depth map of the scene captured by the one or more sensors. In some instances, the dimensioning system may include one or more sensors that are individually or jointly capable of acquiring intensity data corresponding to an intensity image of the scene captured by the one or more sensors. In some instances, the same one or more dimensioning system sensors may acquire both the depth data and the intensity data of the scene captured by the one or more sensors.
However, neither the depth map nor the intensity image may be useful for providing information to the system user. For example, if the dimensioning system has inadvertently omitted one or more three-dimensional objects in the field of view of the dimensioning system sensor, providing an easy, intuitive, way for a user to indicate to the dimensioning system the existence of the three-dimensional object in the field of view of the imaging system image sensor may be advantageous. One potential way to provide an intuitive, easy to use, interface is to provide via an imaging system image sensor a visible image on one or more display devices corresponding to at least a portion of the field of view of the dimensioning system sensor. The dimensioning system could then indicate, for example through the use of an overlay, superimposed wireframe, or bounding element, one or more three-dimensional objects lying within the field of view of the dimensioning system sensor and the imaging system image sensor for which dimensional and volumetric information has been generated by the dimensioning system.
However, the overlay, superimposed wireframe, or bounding element must be displayed in a spatially accurate manner that substantially follows, conforms, or maps to the actual boundaries of the three-dimensional object. To achieve an acceptable degree of accuracy in of spatial mapping, the imaging system image sensor and the dimensioning system sensor should be calibrated or mapped such that the overlay, superimposed wireframe, or bounding element generated by the dimensioning system substantially follows, conforms, or maps to the physical boundaries of the three-dimensional object when the visible image provided by the imaging system image sensor is viewed on the one or more display devices.
Calibrations or mappings between one or more dimensioning system sensors and at least one imaging system image sensor are particularly difficult when the dimensioning system housing the dimensioning system sensor is configured for selective attachment to a wide variety of imaging systems having vastly differing form factors. For example, in some applications the dimensioning system may be physically and communicably coupled to a self service kiosk, while in other applications the same dimensioning system may be physically and communicably coupled to a handheld device such as a handheld scanner, cell phone, or personal digital assistant (“PDA”). In addition to the large variety of devices, the environmental conditions in which the imaging system is used may range from the relatively clean and protected conditions typical of a post office foyer to the relatively exposed and rough-and-tumble environments typical of a warehouse floor or cargo bay.
Spatially mapping the two-dimensional data provided by the imaging system to the three-dimensional data provided by the dimensioning system quickly and reliably while in a pre-run time environment that exists upon communicably coupling the dimensioning system to the imaging system improves the accuracy and acceptance of the dimensioning system by users. It is advantageous to automatically calibrate the dimensioning system sensor with the imaging system image sensor without requiring the use of a specific calibration target. The spatially mapped imaging system and dimensioning system may then enter a run time mode where the dimensioning system is able to provide dimensional and volumetric information on three-dimensional objects placed within the field of view of the dimensioning system. The dimensional and volumetric information may be presented to the user on a display device is coupled to the imaging system in the form of a packaging wireframe model that is spatially mapped to, and concurrently displayed with, the visible image of the three-dimensional object.
Providing the ability to periodically recalibrate the dimensioning system when in run time mode provides a robust, reliable system capable of accurately providing volumetric and dimensional information without requiring time consuming and costly recalibration by trained personnel using calibration targets.
A scene 101 lays within the field of view 116 of the dimensioning system sensor(s) 114 and the field of view 154 of the imaging system image sensor(s) 152. The scene 101 may include any environment, for example a warehouse, a lobby, a service counter, or even an empty room. In
However, despite the differing points of view, sufficient overlap exists between the fields of view of the dimensioning system sensor(s) 114 and the imaging system image sensor(s) 152 such that both the dimensioning system sensor(s) 114 and the imaging system image sensor(s) 152 share a plurality of identifiable three-dimensional points or features existent within the images of the scene 101. Example three-dimensional points or features visible in both the field of view of the dimensioning system sensor(s) 114 and the imaging system image sensor(s) 152 include: a corner of the switch 108a, a first corner of the window 108b, a second corner of the window 108c, a corner of the outlet 108d, the floor/wall joint 108e, the intersection of the floor/wall joint and the wall/wall joint 108f, the intersection of the window frame 108g, and the wall/wall joint 108h (collectively “three-dimensional points 108”). Additional three-dimensional points 108 may exist in the image of the scene 101, however for brevity such points are omitted from the discussion below.
A pre-run time calibration routine is executed by the dimensioning system 110, the imaging system 150, or both the dimensioning system 110 and the imaging system 150 upon detection of the coupling of the dimensioning system 110 to the imaging system 150. The pre-run time calibration routine provides an accurate mapping of the scene 101 as viewed by the dimensioning system sensor(s) 114 to the scene 101 as viewed by the imaging system image sensor(s) 152. In at least some embodiments, the mapping is performed on a point-by-point or pixel-by-pixel basis between the depth and intensity data collected and provided by the dimensioning system 110 and the visible image data collected and provided by the imaging system 150. Upon completion of the pre-run time calibration routine, the dimensioning system 110 is placed into a run time mode in which the dimensioning system 110 can provide volumetric and dimensional information for three-dimensional objects placed in the field of view of the dimensioning system image sensor(s) 114. In at least some instances, the calibration routine may be manually or automatically re-executed by the dimensioning system 110 while in the run time mode.
In at least some situations, the dimensioning system sensor(s) 114 can collect, capture or sense depth and intensity data gathered from the scene 101 appearing in the field of view 116 of the dimensioning system sensor(s) 114. In some instances, the depth and intensity data, either alone or collectively, enable the dimensioning system 110 to identify at least a portion of the three-dimensional points 108 appearing in the scene 101. In some situations, the depth and intensity data may be transmitted from the dimensioning system 110 to the imaging system 150 via the bi-directional data bus(ses) 112 to permit the imaging system 150 to identify at least a portion of the same three-dimensional points 108 appearing in the visible image data collected by the imaging system image sensor(s) 152.
The imaging system image sensor(s) 152 can collect, capture or sense image data corresponding to the scene 101 within the field of view 154. In some instances, the image data may be transmitted from the imaging system 150 to the dimensioning system 110 via the bi-directional data bus(ses) 112 to allow the dimensioning system 110 to identify the same three-dimensional points 108 appearing in the scene 101 as viewed through the field of view 154 of the imaging system image sensor(s) 152. In some instances, the image data may be retained within the imaging system 150 to allow the imaging system 150 to identify the same three-dimensional points 108 appearing in the scene 101 as viewed through the field of view 154 of the imaging system image sensor(s) 152. In other instances, the image data may be transmitted to both the dimensioning system 110 and the imaging system 150 to allow both the dimensioning system 110 and the imaging system 150 to identify the same three-dimensional points 108 appearing in the scene 101 as viewed through the field of view 154 of the imaging system image sensor(s) 152.
The dimensioning system 110, the imaging system 150 or both correlate, associate or otherwise map the three-dimensional points 108 identified in the depth and intensity data provided by the dimensioning system 110 to the same three-dimensional points 108 in the image data provided by the imaging system 150. A number of extrinsic parameters may be determined based on the correlation, association, or mapping between the depth and intensity data provided by the dimensioning system 110 and the image data provided by the imaging system 150. These extrinsic parameters may be useful in providing an algorithmic relationship that spatially maps a three-dimensional point appearing in the depth map and the intensity image provided by the dimensioning system 110 to the same three-dimensional point appearing in the visible image provided by the imaging system 150.
In at least some instances, all or a portion of the number of extrinsic parameters may be used when system 100 is in a run time mode to quickly, accurately, and reliably superimpose a fitted packaging wireframe model generated by the dimensioning system 110 on an image of the three-dimensional object provided by the imaging system 150. The spatial mapping characterized by the number of extrinsic parameters determined during the pre-run time calibration routine permits an accurate fitting of the packaging wireframe model provided by the dimensioning system 110 to the image of the three-dimensional object provided by the imaging system 150. In at least some situations, the packaging wireframe model provided by the dimensioning system 110 may be concurrently displayed on the at least one imaging system display 156 with the visible image of the three-dimensional object provided by the imaging system 150 such that the packaging wireframe model provides an outline or framework about the image of the respective three-dimensional object to which the packaging wireframe model is fitted.
The bi-directional data bus(ses) 112 can include any serial or parallel bus capable of bi-directionally transmitting at least one digital signal. In one preferred embodiment, the bi-directional data bus 112 can be a universal serial bus (“USB”) cable. In some embodiments, the bi-directional data bus(ses) 112 can include one or more wireless radio frequency signals, for example one or more signals conforming to the latest versions of at least one of: the IEEE 802.11a/b/g/n (“WiFi”) signal protocol, the Bluetooth® signal protocol, or the near-field communication (“NFC”) signal protocol. The dimensioning system 110 can be at least partially enclosed within a housing 224. In a preferred embodiment, the housing 224 may detachably coupled to the imaging system 150 using one or more physical couplers 230 such as one or more clips, clamps, or fasteners. The physical couplers 230 may in some instances include one or more “one-way” fittings that freely permit the physical attachment or coupling but resist the detachment of the dimensioning system 110 to the imaging system 150. The use of such “one-way” fittings may be advantageous, for example, in applications where all or a portion of the dimensioning system 110 or imaging system 150 is exposed to the public.
The imaging system 150 can include the imaging system image sensor(s) 152 which is/are communicably coupled to a first bus controller (e.g., a South Bridge processor) 262 via one or more serial or parallel data buses 278, for example a universal serial bus (“USB”), a small computer serial interface (“SCSI”) bus, a peripheral component interconnect (“PCI”) bus, an integrated drive electronics (“IDE”) bus or similar. One or more local busses 264 communicably couple the first bus controller 262 to a second bus controller (e.g., a North Bridge processor) 276. The one or more non-transitory, machine-readable storage media 258 and central processing units (“CPUs”) 260 are communicably coupled to the second bus controller 276 via one or more high-speed or high bandwidth busses 268. The one or more display devices 156 are communicably coupled to the second bus controller 276 via an analog or digital interface 270 such as a Video Graphics Array (“VGA”) interface, a Digital Visual Interface (“DVI”), a High Definition Multimedia Interface (“HDMI”), or similar. In some instances, for example where the one or more display devices 156 include at least one touch-screen display device capable of receiving user input to the imaging system 150, some or all of the one or more display devices 156 may also be communicably coupled to the first bus controller 262, for example via one or more USB interfaces 272.
The dimensioning system 110 is communicably coupled to the imaging system 150 via one or more communication or data interfaces, for example one or more USB bridges coupled to a local or system bus 274 in the imaging system 150. The local or system bus 274 may also be shared with other peripheral devices, such as one or more I/O devices 266, which can include, but not be limited to, one or more keyboards, pointers, touchpads, trackballs, or the like. The imaging system 150 can be of any size, structure, or form factor, including, but not limited to a rack mounted kiosk system, a desktop computer, a laptop computer, a netbook computer, a handheld computer, a tablet computer, a cellular telephone, a personal digital assistant, or the like. Although for clarity and brevity one specific imaging system 150 architecture is presented in detail herein, those of ordinary skill in the art will appreciate that any imaging system 150 architecture may be similarly substituted.
Referring now in detail to the dimensioning system 110, the dimensioning system sensor(s) 114 include any number of devices, systems, or apparatuses suitable for collecting, capturing, or otherwise sensing three-dimensional image data from the scene 101 within the field of view 116 of the dimensioning system sensor(s) 114. Although referred to herein as “three-dimensional image data” it should be understood by one of ordinary skill in the art that the term may apply to more than one three-dimensional image and therefore would equally apply to “three-dimensional video images” which may be considered to comprise a series or time-lapse sequence including a plurality of “three-dimensional images.” The three-dimensional image data acquired or captured by the dimensioning system sensor(s) 114 can include data collected using electromagnetic radiation either falling within the visible spectrum (e.g., wavelengths in the range of about 360 nm to about 750 nm) or falling outside of the visible spectrum (e.g., wavelengths below about 360 nm or above about 750 nm). For example, three-dimensional image data may be collected using infrared, near-infrared, ultraviolet, or near-ultraviolet light. The three-dimensional image data collected by the dimensioning system sensor(s) 114 may include data generated using laser or ultrasonic based imaging technology. In some embodiments, a visible, ultraviolet, or infrared supplemental lighting system (not shown in
In some implementations, the dimensioning system 110 may include a single image sensor 114 capable of acquiring both depth data useful in providing a three-dimensional depth map and intensity data useful in providing an intensity image of the scene 101. The acquisition of depth and intensity data using a single image sensor 114 advantageously eliminates parallax and provides a direct mapping between the depth data in the depth map and the intensity data in the intensity image. The depth map and intensity image may be collected in an alternating sequence by the dimensioning system sensor(s) 114 and the resultant depth data and intensity data stored within the one or more non-transitory, machine-readable storage media 218.
The three-dimensional image data collected, captured or sensed by the dimensioning system sensor(s) 114 may be in the form of an analog signal that is converted to digital data using one or more analog-to-digital (“A/D”) converters (not shown in
The dimensioning system sensor(s) 114 can take a large variety of forms (e.g., digital, analog, still image, molding images) and can be formed from or contain any number of image capture or collection elements, for example picture elements or “pixels.” For example, the dimensioning system sensor(s) 114 can have between 1,000,000 pixels (1 MP) and 100,000,000 pixels (100 MP). The dimensioning system sensor(s) 114 can include any number of current or future developed image sensing devices, collectors, or systems that include, but are not limited to, one or more complementary metal-oxide semiconductor (“CMOS”) image sensors or one or more charge-coupled device (“CCD”) image sensors.
The three-dimensional image data can include more than one type of data associated with or collected, captured or otherwise sensed by each image capture element. For example, in some embodiments, the dimensioning system sensor(s) 114 may capture depth data in the form of a depth map of the three-dimensional objects in the field of view 116 of the dimensioning system sensor(s) 114. The dimensioning system sensor(s) 114 may also capture intensity data in the form of an intensity image of the three-dimensional objects in the field of view 116 of the dimensioning system sensor(s) 114. Where the dimensioning system sensor(s) 114 collect, capture, or otherwise sense more than one type of data, the data in the form of data groups, structures, files or the like may be captured either simultaneously or in an alternating sequence.
The dimensioning system sensor(s) 114 may also provide visible image data capable of rendering a visible black and white, grayscale, or color image of the scene 101. Such visible image data may be communicated to the imaging system 150 via the one or more bi-directional data busses 112 for display on the one or more display devices 156. In some instances, where the dimensioning system sensor(s) 114 is/are able to provide visible image data, the at least one imaging system image sensor 152 may be considered optional and may be omitted.
Data is communicated from the dimensioning system sensor(s) 114 to the non-transitory machine readable storage media 218 via serial or parallel data bus(ses) 226. The non-transitory, machine-readable storage media 218 can be any form of data storage device including, but not limited to, optical data storage, electrostatic data storage, electroresistive data storage, magnetic data storage, and/or molecular data storage devices. All or a portion of the non-transitory, machine-readable storage media 218 may be disposed within the one or more processors 220, for example in the form of a cache, registers, or similar non-transitory memory structure capable of storing data or machine-readable instructions executable by the processor(s) 220.
The non-transitory, machine-readable storage media 218 can have any data storage capacity from about 1 megabyte (1 MB) to about 3 terabytes (3 TB). Two or more storage devices may be used to provide all or a portion of the non-transitory, machine-readable storage media 218. For example, in some embodiments, the non-transitory, machine-readable storage media 218 can include a non-removable portion including a non-transitory, electrostatic, volatile storage medium and a removable portion such as a Secure Digital (SD) card, a compact flash (CF) card, a Memory Stick, or a universal serial bus (“USB”) storage device.
The processor(s) 220 can execute one or more instruction sets that are stored in whole or in part in the non-transitory, machine-readable storage media 218. The machine executable instruction set(s) can include instructions related to basic functional aspects of the one or more processors 220, for example data transmission and storage protocols, communication protocols, input/output (“I/O”) protocols, USB protocols, and the like. Machine executable instruction sets related to all or a portion of the calibration and dimensioning functionality of the dimensioning system 110 and intended for execution by the processor(s) 220 while in calibration or pre-run time mode, in run time mode, or combinations thereof may also be stored within the one or more non-transitory, machine-readable storage media 218, of the processor(s) 220, or within both the non-transitory, machine-readable storage media 218 and the processor(s) 220. Additional dimensioning system 110 functionality may also be stored in the form of machine executable instruction set(s) in the non-transitory, machine-readable storage media 218. Such functionality may include system security settings, system configuration settings, language preferences, dimension and volume preferences, and the like.
The non-transitory, machine-readable storage media 218 may also store machine executable instruction set(s) including one or more auto-executable or batch files intended for execution upon detection of the communicable coupling of the dimensioning system 110 to the imaging system 150. The auto-executable or batch file(s) can initiate the acquisition of depth and intensity data via the dimensioning system sensor(s) 114, the acquisition of image data via the imaging system image sensor(s) 152, and the determination of the number of extrinsic parameters that provide the spatial correspondence between a three-dimensional point 108 as viewed by the dimensioning system sensor(s) 114 with the same three-dimensional point 108 as viewed by the imaging system image sensor(s) 152. In at least some instances, additional machine executable instruction set(s) may be stored in the non-transitory, machine-readable storage media 218 to periodically repeat the acquisition of depth and intensity data via the dimensioning system sensor(s) 114, the acquisition of image data via the imaging system image sensor(s) 152, and the determination of the number of extrinsic parameters either automatically, for example on a regular or scheduled basis, or manually at the direction of a user or a system administrator.
Data is transferred between the non-transitory, machine-readable storage media 218 and the processor(s) 220 via serial or parallel bi-directional data bus(ses) 228. The processor(s) 220 can include any device comprising one or more cores or independent central processing units that are capable of executing one or more machine executable instruction sets. The processor(s) 220 can, in some embodiments, include a general purpose processor such as a central processing unit (“CPU”) including, but not limited to, an Intel® Atom® processor, an Intel® Pentium®, Celeron®, or Core 2® processor, and the like. In other embodiments the processor(s) 220 can include a system-on-chip (“SoC”) architecture, including, but not limited to, the Intel® Atom® System on Chip (“Atom SoC”) and the like. In other embodiments, the processor(s) 220 can include a dedicated processor such as an application specific integrated circuit (“ASIC”), a programmable gate array (“PGA” or “FPGA”), a digital signal processor (“DSP”), or a reduced instruction set computer (“RISC”) based processor. Where the dimensioning system 110 or the imaging system 150 is a battery-powered portable system, the processor(s) 220 can include low power consumption processor(s), for example Intel® Pentium M®, or Celeron M® mobile system processors or the like, to extend the system battery life. In at least some instances, power for the dimensioning system 110 may be supplied by the imaging system 150 via bi-directional data bus(ses) 112 or via a dedicated power supply.
Data in the form of three-dimensional image data, packaging wireframe model data, instructions, input/output requests and the like may be bi-directionally transferred between the dimensioning system 110 and the imaging system 150 via the bi-directional data bus(ses) 112. Within the imaging system 150, the packaging wireframe model data can, for example, be combined with visual image data collected, captured or otherwise sensed by the imaging system image sensor(s) 152 to provide a display output including a visual image of one or more three-dimensional objects 102 appearing in the imaging system image sensor(s) 152 field of view 154 concurrently with an image of the fitted packaging wireframe model provided by the dimensioning system 110.
In at least some embodiments, the dimensioning system 110 including the dimensioning system sensor(s) 114, the non-transitory, machine-readable storage media 218, and the processor(s) 220 are functionally combined to provide a run-time system capable rendering a packaging wireframe model that is scaled and fitted to the one or more three-dimensional objects appearing in the field of view 116.
Referring now in detail to the imaging system 150, the imaging system image sensor(s) 152 can collect, capture or otherwise sense visual image data of the scene 101 within the field of view 154 of the imaging system image sensor(s) 152. As a device that is discrete from the dimensioning system sensor(s) 114, the imaging system image sensor(s) 152 will have a field of view 154 that differs from the field of view 116 of the dimensioning system sensor(s) 114. In at least some embodiments, the CPU(s) 260, the processor(s) 220, or a combination of the CPU(s) 260 and processor(s) 220 may execute pre-run time and run time calibration routines to spatially map the visible image data collected by the imaging system image sensor(s) 152 to the depth and intensity data collected by the dimensioning system sensor(s) 114.
The imaging system image sensor(s) 152 can take any of a large variety of forms (e.g., digital, analog, still image, moving image) and can be formed from or contain any number of image capture or collection elements, for example picture elements or “pixels.” For example, the imaging system image sensor(s) 152 may have between 1,000,000 pixels (1 MP) and 100,000,000 pixels (100 MP). The visual image data collected, captured or otherwise sensed by the imaging system image sensor(s) 152 may originate as an analog signal that is converted to digital visual image data using one or more internal or external analog-to-digital (“A/D”) converters (not shown in
In some embodiments, the imaging system image sensor(s) 152 may collect, capture, or sense more than one type of data. For example, the imaging system image sensor(s) 152 may acquire visual image data of the scene 101 in the field of view 154 of the imaging system image sensor(s) 152, and/or infrared image data of the scene 101. Where the imaging system image sensor(s) 152 collects, captures, or otherwise senses more than one type of image data, the image data may be organized into one or more data sets, structures, files, or the like. Where the imaging system image sensor(s) 152 collect, capture, or otherwise sense more than one type of data, the data may be collected, captured, or sensed either simultaneously or in an alternating sequence by the imaging system image sensor(s) 152. At least a portion of the visual image data collected by the imaging system image sensor(s) 152 is stored in the form of one or more data sets, structures, or files in the non-transitory, machine-readable storage media 258.
Image data is transferred between the imaging system image sensor(s) 152 and the non-transitory, machine-readable storage media 258 via the first bus controller 262, the second bus controller 276 and the serial or parallel data busses 264, 268. The image data provided by the imaging system image sensor(s) 152 can be stored within the non-transitory, machine-readable storage media 258 in one or more data sets, structures, or files. The non-transitory, machine-readable storage media 258 can have any data storage capacity from about 1 megabyte (1 MB) to about 3 terabytes (3 TB). In some embodiments two or more storage devices may form all or a portion of the non-transitory, machine-readable storage media 258. For example, in some embodiments, the non-transitory, machine-readable storage media 258 may include a non-removable portion including a non-transitory, electrostatic, volatile storage medium and a removable portion such as a Secure Digital (SD) card, a compact flash (CF) card, a Memory Stick, or a universal serial bus (“USB”) storage device.
Data is transferred between the non-transitory, machine-readable storage media 258 and the CPU(s) 260 via the second bus controller 276 and one or more serial or parallel bi-directional data busses 268. The CPU(s) 260 can include any device comprising one or more cores or independent central processing units that are capable of executing one or more machine executable instruction sets. The CPU(s) 260 can, in some embodiments, include a general purpose processor including, but not limited to, an Intel® Atom® processor, an Intel® Pentium®, Celeron®, or Core 2® processor, and the like. In other embodiments the CPU(s) 260 can include a system-on-chip (“SoC”) architecture, including, but not limited to, the Intel® Atom® System on Chip (“Atom SoC”) and the like. In other embodiments, the CPU(s) 260 can include a dedicated processor such as an application specific integrated circuit (“ASIC”), a programmable gate array (“PGA” or “FPGA”), a digital signal processor (“DSP”), or a reduced instruction set computer (“RISC”) based processor. Where the imaging system 150 is a battery-powered portable system, the CPU(s) 260 can include one or more low power consumption processors, for example Intel® Pentium M®, or Celeron M® mobile system processors or the like, to extend the system battery life.
The imaging system 150 may have one or more discrete graphical processing units (“GPUs”—not shown in
One or more peripheral I/O devices 266 may be communicably coupled to the imaging system 150 to facilitate the receipt of user input by the imaging system 150 via a pointer, a keyboard, a touchpad, or the like. In at least some embodiments the peripheral I/O device(s) 266 may be USB devices that are communicably coupled via a USB bridge to the local bus 274.
In run time mode, the dimensioning system sensor(s) 114 can collect, capture, or otherwise sense depth data corresponding to a depth map and intensity data corresponding to an intensity image of the three-dimensional object 302. Contemporaneously, the imaging system image sensor(s) 152 can collect, capture or otherwise sense visual image data corresponding to a visual image of the three-dimensional object 302. Based on the depth map and intensity image, the processor(s) 220 scale and fit a packaging wireframe model 306 to the three-dimensional object 302. The processor(s) 220, CPU(s) 260, or any combination thereof can superimpose or overlay the packaging wireframe model 306 on the visible image of the three-dimensional object 302 to provide a display image depicting both the image of the three-dimensional object 304 concurrently with the superimposed or overlaid packaging wireframe model 306.
After determining the number of extrinsic parameters in pre-run time mode, the dimensioning system 110 may enter a run time mode. In the run time mode, the dimensioning system 110 scales and fits packaging wireframe models 306 to the three-dimensional objects 302 which appear the field of view 116 of the dimensioning system sensor(s) 114. In at least some instances, the scaled and fitted packaging wireframe models 306 generated by the dimensioning system 110 are displayed overlaid or superimposed on an image of the three-dimensional object 304 by the imaging system display(s) 156.
At 402, the dimensioning system 110 detects the communicable coupling of an imaging system 150, for example by detecting the coupling of the bi-directional data bus(ses) 112 to the imaging system 150. In at least some instances, the dimensioning system 110 may be physically coupled to the imaging system 150 via the one or more physical couplers 230. In at least some instances, the dimensioning system 110 can detect the physical coupling of the imaging system 150. In at least some instances, responsive to the detection of the physical or communicable coupling of the imaging system 150 to the dimensioning system 110, a pre-run time machine executable instruction set may be retrieved from the non-transitory, machine-readable storage media 218 and executed by the processor(s) 220.
At 404, responsive to the execution of the pre-run time machine executable instruction set by the processor(s) 220, the dimensioning system 110 collects, captures or otherwise senses depth data corresponding to a depth image of the scene 101 within the field of view 116 of the dimensioning system sensor(s) 114. In some instances, the scene 101 may not include one or more calibration targets and instead may only contain an image of the environment, area, or volume proximate or in a line of sight of the dimensioning system 110. In at least some instances, at least a portion of the depth data acquired by the dimensioning system sensor(s) 114 can include one or more three-dimensional points corresponding to features detectible in the depth map. In some instances, the scene 101 may be illuminated using a structured or modulated light pattern to assist the dimensioning system 110 in capturing depth data to provide the depth map of the scene 101. In some instances, at least one of the exposure or gain of the dimensioning system sensor(s) 114 may be compensated or adjusted when a structured or modulated light pattern assists in the acquisition or collection of depth data to provide the depth map of the scene 101.
At 406, responsive to the execution of the pre-run time machine executable instruction set by the processor(s) 220, the dimensioning system 110 collects, captures or otherwise senses intensity data corresponding to an intensity image of the scene 101 within the field of view 116 of the dimensioning system sensor(s) 114. In some instances the scene 101 may not include one or more calibration targets and instead may only contain an image of the environment, area, or volume proximate or in a line of sight of the dimensioning system 110. In at least some instances, at least a portion of the intensity image acquired by the dimensioning system sensor(s) 114 can include one or more three-dimensional points corresponding to features detectible in the intensity image. At least a portion of the three-dimensional points detected by the dimensioning system 110 in the intensity image may correspond to at least a portion of the three-dimensional points detected by the dimensioning system 110 in the depth map data acquired in 404. In some instances, the scene 101 may be illuminated using a structured or modulated light pattern to assist the dimensioning system 110 in capturing intensity data to provide the intensity image of the scene 101. In some instances, at least one of the exposure or gain of the dimensioning system sensor(s) 114 may be compensated or adjusted when a structured or modulated light pattern assists in the acquisition or collection of intensity data to provide the intensity image of the scene 101.
At 408, responsive to the execution of the pre-run time machine executable instructions by the processor(s) 220, the dimensioning system 110 acquires or receives visible image data from the imaging system 150. The visible image data may be collected, captured, or otherwise sensed by the imaging system 150 using the imaging system image sensor(s) 152 and transmitted to the dimensioning system 110 via the bi-directional data bus(ses) 112.
At 410 the processor(s) 220 determines a number of extrinsic parameters spatially mapping one or more three-dimensional points in the depth map and intensity image provided by the dimensioning system 110 to the same one or more three-dimensional points in the visible image provided by the imaging system 150. In at least some instances, the number of extrinsic parameters may be calculated by determining a number of points positioned on or associated with at least one feature detectible in the depth and intensity data provided by the dimensioning system sensor(s) 114 and determining an equal number of respective points similarly positioned on or associated with the at least one feature detectible in the imaging system image data provided by the imaging system image sensor(s) 152.
In some instances, the processor(s) 220 may determine a minimum of eight three-dimensional points positioned on or associated with one or more features detectible in the depth and intensity data. Each of the points identified by the processor(s) 220 in the depth and intensity data may be identified based upon the three-dimensional coordinates (xi, yi, zi) associated with each point. In some instances, the processor(s) 220 may determine an equal number of points similarly positioned on or associated with the at least one feature detectible in the visible image data. Each of the points identified by the processor(s) 220 in the visible image data are identified based upon two-dimensional coordinates (xc, yc) associated with each point. The processor(s) 220 also determine a back focus (fc) of the imaging system image sensor(s) 152.
In at least some instances, at least two of the extrinsic parameters can include a three-dimensional, three-by-three, rotation matrix (R11-33) and a three-dimensional, one-by-three, translation matrix (T0-2) that spatially relate the depth map and intensity image provided by the dimensioning system sensor(s) 114 to the visible image provided by the imaging system image sensor(s) 152.
In at least some embodiments, the components of the rotation and translation matrix are determined using the point correspondence determined by the processor(s) 220 and the known back-focus of the imaging system image sensor(s) 152 using the following relationships:
At 412 after successfully determining the number of extrinsic parameters linking the depth map and intensity image provided by the dimensioning system 110 to the visible image provided by the imaging system 150, the dimensioning system 110 may be placed into or otherwise enter a run time mode.
The pre-run time calibration method 400 (
At 502, the dimensioning system 110 can generate a packaging wireframe model 306 corresponding to the boundaries of a three-dimensional object 302 appearing on the field of view of the dimensioning system sensor(s) 114. The dimensioning system 110 may generate the packaging wireframe model 306 using any shape recognition and wireframe generation algorithm. In at least one instance, upon detecting a presence of a three-dimensional object 302 within the field of view 116 of the dimensioning system sensor(s) 114, the processor(s) 220 select one or more geometric primitives from a library of geometric primitives stored in the non-transitory, machine-readable storage media 218. The processor(s) 220 scale and fit the selected geometric primitive(s) to substantially match, virtually simulate, or otherwise encompass the three-dimensional object 302. The processor(s) 220 fit a packaging wireframe model 306 about the one or more scaled and fitted geometric primitives. Due to the previously determined extrinsic parameters, the packaging wireframe model 306 as scaled and fitted to the geometric primitive(s) by the dimensioning system 110 will substantially align with or encompass the boundaries or edges of the image of the three-dimensional object 304 provided by the imaging system 150.
At 504, the imaging system 150 concurrently displays the packaging wireframe model 306 provided by the dimensioning system 110 with the image of the three-dimensional object 304 on the imaging system display(s) 156. In at least some instances, the packaging wireframe model 306 is depicted in a bold or contrasting color to distinguish the packaging wireframe model 306 from the background and the image of the three-dimensional object 304.
At 602, the system 100 queries whether a manual run time calibration input has been received by either the dimensioning system 110 or the imaging system 150. If a manual run time calibration input has been received, a run time calibration routine is initiated at 606. If a manual run time calibration input has not been received, at 604 the system 100 queries whether an automatic run time calibration input has been received by either the dimensioning system 110 or the imaging system 150. If an automatic run time calibration input has been received, the run time calibration routine is initiated at 606. If an automatic run time calibration input has not been received, the system 100 continues to query for the receipt of a manual or automatic run time calibration input by either the dimensioning system 110 or the imaging system 150.
At 606, responsive to the receipt of either a manual or an automatic run time calibration input by the dimensioning system 110 or the imaging system 150, the dimensioning system 110 collects, captures, or otherwise senses depth data corresponding to a depth image of the scene 101 within the field of view 116 of the dimensioning system sensor(s) 114. In some instances, the scene 101 may not include one or more calibration targets and instead may only contain a three-dimensional object or an image of the environment, area, or volume proximate or in the line of sight of the dimensioning system 110. In at least some instances, at least a portion of the depth data acquired by the dimensioning system sensor(s) 114 can include one or more three-dimensional points corresponding to features detectible in the depth map. In some instances, the scene 101 may be illuminated using a structured or modulated light pattern to assist the dimensioning system 110 in capturing depth data to provide the depth map of the scene 101. In some instances, at least one of the exposure or gain of the dimensioning system sensor(s) 114 may be compensated or adjusted when a structured or modulated light pattern assists in the acquisition or collection of depth data to provide the depth map of the scene 101.
At 608, the dimensioning system 110 collects, captures, or otherwise senses intensity data corresponding to an intensity image of the scene 101 within the field of view 116 of the dimensioning system sensor(s) 114. In some instances the scene 101 may not include one or more calibration targets and instead may only contain a three-dimensional object or an image of the environment, area, or volume proximate or in the line of sight of the dimensioning system 110. In at least some instances, at least a portion of the intensity image acquired by the dimensioning system sensor(s) 114 can include one or more three-dimensional points corresponding to features detectible in the intensity image. At least a portion of the three-dimensional points detected by the dimensioning system 110 in the intensity image may correspond to at least a portion of the three-dimensional points detected by the dimensioning system 110 in the depth map data acquired at 606. In some instances, the scene 101 may be illuminated using a structured or modulated light pattern to assist the dimensioning system 110 in capturing intensity data to provide the intensity image of the scene 101. In some instances, at least one of the exposure or gain of the dimensioning system sensor 114 may be compensated or adjusted when a structured or modulated light pattern assists in the acquisition or collection of intensity data to provide the intensity image of the scene 101.
At 610, the dimensioning system 110 acquires or receives visible image data from the imaging system 150. The visible image data is collected, captured or otherwise sensed by the imaging system 150 using the imaging system image sensor(s) 152 and transmitted to the dimensioning system 110 via the bi-directional data bus(ses) 112.
At 612 the dimensioning system processor(s) 220 can determine a number of extrinsic parameters spatially mapping one or more three-dimensional points in the depth map and intensity image provided by the dimensioning system 110 to the same one or more three-dimensional points in the visible image provided by the imaging system 150. In at least some instances, the number of extrinsic parameters may be calculated by determining a number of points positioned on or associated with at least one feature detectible in the depth and intensity data provided by the dimensioning system sensor(s) 114 and determining an equal number of respective points similarly positioned on or associated with the at least one feature detectible in the imaging system image data provided by the imaging system image sensor(s) 152.
In some instances, the processor(s) 220 may determine a minimum of eight three-dimensional points positioned on or associated with one or more features detectible in the depth and intensity data. Each of the points identified by the processor(s) 220 in the depth and intensity data may be identified based upon the three-dimensional coordinates (xi, yi, zi) associated with each point. In some instances, the processor(s) 220 may determine an equal number of points similarly positioned on or associated with the at least one feature detectible in the visible image data. Each of the points identified by the processor(s) 220 in the visible image data are identified based upon two-dimensional coordinates (xc, yc) associated with each point. The processor(s) 220 also determine a back focus (fc) of the imaging system image sensor(s) 152.
In at least some instances, at least two of the extrinsic parameters can include a three-dimensional, three-by-three, rotation matrix (R11-33) and a three-dimensional, one-by-three, translation matrix (T0-2) that spatially relate the depth map and intensity image provided by the dimensioning system sensor(s) 114 to the visible image provided by the imaging system image sensor(s) 152.
In at least some embodiments, the components of the rotation and translation matrix are determined using the point correspondence determined by the processor(s) 220 and the known back-focus of the imaging system image sensor(s) 152 using the following relationships:
The foregoing detailed description has set forth various embodiments of the devices and/or processes via the use of block diagrams, schematics, and examples. Insofar as such block diagrams, schematics, and examples contain one or more functions and/or operations, it will be understood by those skilled in the art that each function and/or operation within such block diagrams, flowcharts, or examples can be implemented, individually and/or collectively, by a wide range of hardware, software, firmware, or virtually any combination thereof. In one embodiment, the present subject matter may be implemented via Application Specific Integrated Circuits (ASICs) or programmable gate arrays. However, those skilled in the art will recognize that the embodiments disclosed herein, in whole or in part, can be equivalently implemented in standard integrated circuits, as one or more computer programs running on one or more computers (e.g., as one or more programs running on one or more computer systems), as one or more programs running on one or more controllers (e.g., microcontrollers) as one or more programs running on one or more processors (e.g., microprocessors), as firmware, or as virtually any combination thereof, and that designing the circuitry and/or writing the code for the software and or firmware would be well within the skill of one of ordinary skill in the art in light of this disclosure.
Various methods and/or algorithms have been described. Some or all of those methods and/or algorithms may omit some of the described acts or steps, include additional acts or steps, combine acts or steps, and/or may perform some acts or steps in a different order than described. Some of the method or algorithms may be implemented in software routines. Some of the software routines may be called from other software routines. Software routines may execute sequentially or concurrently, and may employ a multi-threaded approach.
In addition, those skilled in the art will appreciate that the mechanisms taught herein are capable of being distributed as a program product in a variety of forms, and that an illustrative embodiment applies equally regardless of the particular type of signal bearing non-transitory media used to actually carry out the distribution. Examples of non-transitory signal bearing media include, but are not limited to, the following: recordable type media such as portable disks and memory, hard disk drives, CD/DVD ROMs, digital tape, computer memory, and other non-transitory computer-readable storage media.
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.
The present application claims the benefit of U.S. patent application Ser. No. 13/465,968 for Dimensioning System Calibration Systems and Methods filed May 7, 2012 (and published Nov. 7, 2013 as U.S. Patent Application Publication No. 2013/0293540), now U.S. Pat. No. 9,007,368. Each of the foregoing patent application, patent publication, and patent is hereby incorporated by reference in its entirety. The present application is related to U.S. patent application Ser. No. 13/464,799 for Volume Dimensioning Systems and Methods filed May 4, 2012 (and published Nov. 7, 2013 as U.S. Patent Application Publication No. 2013/0293539) and International Application No. PCT/US13/39438 for Volume Dimensioning Systems and Methods filed May 3, 2013 (and published Nov. 7, 2013 as WIPO Publication No. WO 2013/166368). Each of the foregoing patent applications and patent publications is hereby incorporated by reference in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
3971065 | Bayer | Jul 1976 | A |
4398811 | Nishioka et al. | Aug 1983 | A |
4730190 | Win et al. | Mar 1988 | A |
5220536 | Stringer et al. | Jun 1993 | A |
5331118 | Jensen | Jul 1994 | A |
5359185 | Hanson | Oct 1994 | A |
5548707 | LoNegro et al. | Aug 1996 | A |
5555090 | Schmutz | Sep 1996 | A |
5590060 | Granville et al. | Dec 1996 | 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 |
5734476 | Dlugos | Mar 1998 | A |
5831737 | Stringer et al. | Nov 1998 | A |
5850370 | Stringer et al. | 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 |
5969823 | Wurz et al. | Oct 1999 | A |
5978512 | Kim | Nov 1999 | A |
5979760 | Freyman et al. | Nov 1999 | A |
5991041 | Woodworth | Nov 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 |
6069696 | McQueen et al. | May 2000 | A |
6137577 | Woodworth | Oct 2000 | A |
6177999 | Wurz et al. | Jan 2001 | B1 |
6246468 | Dimsdale | Jun 2001 | B1 |
6336587 | He et al. | Jan 2002 | B1 |
6369401 | Lee | Apr 2002 | B1 |
6373579 | Ober et al. | Apr 2002 | B1 |
6457642 | Good et al. | Oct 2002 | B1 |
6517004 | Good et al. | Feb 2003 | B2 |
6674904 | McQueen | Jan 2004 | B1 |
6705526 | Zhu et al. | Mar 2004 | B1 |
6781621 | Gobush et al. | Aug 2004 | B1 |
6824058 | Patel et al. | Nov 2004 | B2 |
6832725 | Gardiner et al. | Dec 2004 | B2 |
6858857 | Pease et al. | Feb 2005 | B2 |
6971580 | Zhu et al. | Dec 2005 | B2 |
7085409 | Sawhney et al. | Aug 2006 | B2 |
7086162 | Tyroler | Aug 2006 | B2 |
7104453 | Zhu et al. | Sep 2006 | B1 |
7128266 | Zhu et al. | Oct 2006 | B2 |
7159783 | Walczyk et al. | Jan 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 | May 2009 | B2 |
7586049 | Wurz | Sep 2009 | B2 |
7602404 | Reinhardt et al. | Oct 2009 | B1 |
7726575 | Wang et al. | Jun 2010 | B2 |
7788883 | Buckley et al. | Sep 2010 | B2 |
7974025 | Topliss | Jul 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 |
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 |
8212889 | Chanas et al. | Jul 2012 | B2 |
8228510 | Pangrazio et al. | Jul 2012 | B2 |
8294969 | Plesko | 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 |
8322622 | Liu | Dec 2012 | B2 |
8339462 | Stec et al. | Dec 2012 | B2 |
8350959 | Topliss et al. | Jan 2013 | B2 |
8366005 | Kotlarsky et al. | Feb 2013 | B2 |
8371507 | Haggerty et al. | 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 |
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 |
8763909 | 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 |
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 |
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 |
8903172 | Smith | Dec 2014 | B2 |
8908995 | Benos et al. | 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 |
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 |
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 |
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 |
20010032879 | He et al. | Oct 2001 | A1 |
20020118874 | Chung et al. | Aug 2002 | A1 |
20020179708 | Zhu 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 |
20040024754 | Mane et al. | Feb 2004 | A1 |
20040066329 | Zeitfuss et al. | Apr 2004 | A1 |
20040155975 | Hart et al. | Aug 2004 | A1 |
20040165090 | Ning | Aug 2004 | A1 |
20040211836 | Patel et al. | Oct 2004 | A1 |
20040233461 | Armstrong et al. | Nov 2004 | A1 |
20050006477 | Patel | Jan 2005 | A1 |
20050117215 | Lange | Jun 2005 | A1 |
20050128196 | Popescu et al. | Jun 2005 | 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 |
20070031064 | Zhao et al. | Feb 2007 | A1 |
20070063048 | Havens et al. | Mar 2007 | A1 |
20070181685 | Zhu et al. | Aug 2007 | A1 |
20070237356 | Dwinell et al. | Oct 2007 | A1 |
20080013793 | Hillis et al. | Jan 2008 | A1 |
20080035390 | Wurz | Feb 2008 | A1 |
20080056536 | Hildreth et al. | Mar 2008 | A1 |
20080164074 | Wurz | Jul 2008 | A1 |
20080212168 | Olmstead et al. | Sep 2008 | A1 |
20090059004 | Bochicchio | Mar 2009 | A1 |
20090134221 | Zhu et al. | May 2009 | A1 |
20090237411 | Gossweiler et al. | Sep 2009 | A1 |
20090268023 | Hsieh | Oct 2009 | A1 |
20090313948 | Buckley et al. | Dec 2009 | A1 |
20090323084 | Dunn et al. | Dec 2009 | A1 |
20100035637 | Varanasi et al. | Feb 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 et al. | Aug 2010 | A1 |
20100208039 | Stettner | Aug 2010 | A1 |
20100220894 | Ackley et al. | Sep 2010 | A1 |
20110099474 | Grossman et al. | Apr 2011 | A1 |
20110169999 | Grunow et al. | Jul 2011 | A1 |
20110202554 | Powilleit et al. | Aug 2011 | A1 |
20110249864 | Venkatesan et al. | Oct 2011 | A1 |
20110279916 | Brown et al. | Nov 2011 | A1 |
20110286007 | Pangrazio et al. | Nov 2011 | A1 |
20120024952 | Chen | Feb 2012 | A1 |
20120056982 | Katz et al. | Mar 2012 | A1 |
20120074227 | Ferren et al. | Mar 2012 | A1 |
20120081714 | Pangrazio et al. | Apr 2012 | A1 |
20120111946 | Golant | May 2012 | A1 |
20120168512 | Kotlarsky et al. | Jul 2012 | A1 |
20120185094 | Rosenstein et al. | Jul 2012 | A1 |
20120193423 | Samek | Aug 2012 | A1 |
20120197464 | Wang et al. | Aug 2012 | A1 |
20120203647 | Smith | Aug 2012 | A1 |
20120218436 | Rodriguez et al. | Aug 2012 | A1 |
20120223141 | Good et al. | Sep 2012 | A1 |
20120224026 | Bayer et al. | Sep 2012 | A1 |
20120242852 | Hayward et al. | Sep 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 |
20120294549 | Doepke | Nov 2012 | A1 |
20120299961 | Ramkumar et al. | Nov 2012 | A1 |
20120300991 | Free | Nov 2012 | A1 |
20120313848 | Galor et al. | Dec 2012 | A1 |
20130043312 | Van Horn | Feb 2013 | A1 |
20130050426 | Sarmast et al. | Feb 2013 | A1 |
20130075168 | Amundsen et al. | Mar 2013 | A1 |
20130101158 | Lloyd et al. | Apr 2013 | A1 |
20130175341 | Kearney et al. | Jul 2013 | A1 |
20130175343 | Good | Jul 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 |
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 |
20130308625 | Corcoran | Nov 2013 | A1 |
20130313324 | Koziol et al. | Nov 2013 | A1 |
20130313325 | Wilz et al. | Nov 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 |
20140025584 | Liu et al. | Jan 2014 | A1 |
20140034731 | Gao et al. | Feb 2014 | A1 |
20140034734 | Sauerwein | Feb 2014 | A1 |
20140036848 | Pease 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 |
20140061306 | Wu et al. | Mar 2014 | A1 |
20140063289 | Hussey et al. | Mar 2014 | A1 |
20140066136 | Sauerwein et al. | Mar 2014 | A1 |
20140067692 | Ye et al. | Mar 2014 | A1 |
20140070005 | Nahill 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 |
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 | Giordano et al. | Apr 2014 | A1 |
20140104451 | Todeschini et al. | 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 |
20140136208 | Maltseff et al. | May 2014 | A1 |
20140140585 | Wang | May 2014 | A1 |
20140151453 | Meier et al. | Jun 2014 | A1 |
20140152882 | Samek et al. | 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 |
20140168787 | Wang et al. | Jun 2014 | A1 |
20140175165 | Havens et al. | Jun 2014 | A1 |
20140175172 | Jovanovski et al. | Jun 2014 | A1 |
20140191644 | Chaney | Jul 2014 | A1 |
20140191913 | Ge et al. | Jul 2014 | A1 |
20140197238 | Lui et al. | Jul 2014 | A1 |
20140197239 | Havens et al. | Jul 2014 | A1 |
20140197304 | Feng et al. | Jul 2014 | A1 |
20140203087 | Smith et al. | Jul 2014 | A1 |
20140204268 | Grunow et al. | Jul 2014 | A1 |
20140214631 | Hansen | Jul 2014 | A1 |
20140217166 | Berthiaume et al. | Aug 2014 | A1 |
20140217180 | Liu | Aug 2014 | A1 |
20140231500 | Ehrhart et al. | Aug 2014 | A1 |
20140232930 | Anderson | Aug 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 |
20140270196 | Braho et al. | Sep 2014 | A1 |
20140270229 | Braho | 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 |
20140312121 | Lu 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 |
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 |
20150001301 | Ouyang | Jan 2015 | A1 |
20150001304 | Todeschini | Jan 2015 | A1 |
20150003673 | Fletcher | 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 |
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 |
20150063215 | Wang | Mar 2015 | A1 |
20150063676 | Lloyd et al. | Mar 2015 | A1 |
20150069130 | Gannon | 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 |
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 |
20150169925 | Chang et al. | Jun 2015 | A1 |
20150169929 | Williams 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 |
20150204671 | Showering | Jul 2015 | A1 |
20150213647 | Laffargue et al. | Jul 2015 | A1 |
Number | Date | Country |
---|---|---|
10210813 | Oct 2003 | DE |
102007037282 | Mar 2008 | DE |
2381421 | Oct 2011 | EP |
2722656 | Apr 2014 | EP |
2779027 | Sep 2014 | EP |
2843590 | Mar 2015 | EP |
2845170 | Mar 2015 | EP |
2008210276 | Sep 2008 | JP |
20110013200 | Feb 2011 | KR |
20110117020 | Oct 2011 | KR |
20120028109 | Mar 2012 | KR |
2006095110 | Sep 2006 | WO |
2007015059 | Feb 2007 | WO |
2013033442 | Mar 2013 | WO |
2013163789 | Nov 2013 | WO |
2013166368 | Nov 2013 | WO |
2013173985 | Nov 2013 | WO |
2014019130 | Feb 2014 | WO |
2014110495 | Jul 2014 | WO |
Entry |
---|
Peter Clarke, Actuator Developer 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 of 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 pages 7. |
International Search Report for PCT/US2013/039438 (WO2013166368), 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-X/96 1996 IEEE; 4 pages. |
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. |
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 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. 14/800,757 , Eric Todeschini, filed Jul. 16, 2015, not published yet, Dimensioning and Imaging Items, 80 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. 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. |
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. |
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. |
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. 14/724,134 for Electronic Device With Wireless Path Selection Capability filed May 28, 2015 (Wang et al.); 42 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. 14/724,849 for Method of Programming the Default Cable Interface Software in an Indicia Reading Device filed May 29, 2015 (Barten); 29 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. 14/722,608 for Interactive User Interface for Capturing a Document in an Image Signal filed May 27, 2015 (Showering et al.); 59 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. 14/724,908 for Imaging Apparatus Having Imaging Assembly filed May 29, 2015 (Barber et al.); 39 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. 14/679,275 for Dimensioning System Calibration Systems and Methods filed Apr. 6, 2015 (Laffargue et al.); 47 pages. |
U.S. Appl. No. 14/744,633 for Imaging Apparatus Comprising Image Sensor Array Having Shared Global Shutter Circuitry filed Jun. 19, 2015 (Wang); 65 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. 14/744,836 for Cloud-Based System for Reading of Decodable Indicia filed Jun. 19, 2015 (Todeschini et al.); 26 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. 14/745,006 for Selective Output of Decoded Message Data filed Jun. 19, 2015 (Todeschini et al.); 36 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. |
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. 29/519,017 for Scanner filed Mar. 2, 2015 (Zhou et al.); 11 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. 14/529,857 for Barcode Reader With Security Features filed Oct. 31, 2014 (Todeschini et al.); 32 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. 14/662,922 for Multifunction Point of Sale System filed Mar. 19, 2015 (Van Horn et al.); 41 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. 14/533,319 for Barcode Scanning System Using Wearable Device With Embedded Camera filed Nov. 5, 2014 (Todeschini); 29 pages. |
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. |
Number | Date | Country | |
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20150213647 A1 | Jul 2015 | US |
Number | Date | Country | |
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Parent | 13465968 | May 2012 | US |
Child | 14679275 | US |