Augmented reality refers to using computer generated enhancements to add new information into images in a real-time or near real-time fashion. For example, video images of a wall output on a display of a device may be enhanced with display details that are not present on the wall, but that are generated to appear as if they are on the wall by an augmented reality system. Such systems require a complex mix of image capture information that is integrated and matched with the augmented reality information that is to be added to a captured scene in a way that attempts to seamlessly present a final image from a perspective determined by the image capture device.
Various ones of the appended drawings merely illustrate example embodiments of the present disclosure and should not be considered as limiting its scope.
The following relates to augmented reality image processing and image based tracking. Some particular embodiments describe using an initial rough location estimate to identify façade data about local buildings. An image captured for an augmented reality system may then be compared with the façade data. This comparison attempts to match some or all of a building façade against a portion of the captured image. Location and perspective information from the façade data may be used along with an identified matching portion of the captured image to generate a second estimate of the location associated with the perspective of the captured image. This second, more accurate location may then be used to place virtual items within the captured image or subsequent related captured images as part of an augmented reality display.
The description that follows includes systems, devices, and methods that illustrate embodiments of the disclosure. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide an understanding of various embodiments of the inventive subject matter. It will be evident, however, to those skilled in the art, that embodiments of the inventive subject matter may be practiced without these specific details.
Augmented reality, as described herein, refers to systems and devices that capture images, enhance those images with additional information, and then present the enhanced information on a display. This enables, for example, a user to hold up a phone to capture a video stream of a scene, and an output display of the phone to present the scene as visible to the user along with additional information. This information may include placing virtual objects in the scene so the virtual objects are presented as if they existed in the scene. Aspects of such virtual objects are processed to occlude the virtual object if another real or virtual object passes in front of the virtual object as shown from the perspective of the image sensor capturing the environment. Such virtual objects are also processed to maintain their relationship with real objects as both real and virtual objects move over time, and as the perspective of the image sensor capturing the environment changes.
One issue that arises with such augmented reality scenes including both real objects and virtual objects is setting and maintaining a tracking between the real objects and the virtual objects. This tracking is important to maintaining an immersive presentation of the virtual objects within the environment and treating the virtual objects as if they were real within the environment. Failed tracking creates jitter or unexpected movement of the virtual item within a scene, or may set an initial virtual object placement that overlaps or is out of synchronization with real objects in unnatural ways.
Simultaneous location and mapping (SLAM) systems are systems that are used to track key points in two dimensional image frames of video, and to identify three-dimensional objects from the image frames as well as a relative location of the camera to those objects. Such processing to identify three-dimensional objects, however, is processor and memory intensive.
A “façade” as used herein refers to details of a building or physical structure, including details of building walls. The real world environment of a building may include significant three-dimensional texture, but as used herein, a façade includes portions of a wall or building that may be modeled as two-dimensional. This particularly includes patterns such as murals or other images that may be part of a building's wall surfaces. Façade data for a building may include a simplified two-dimensional model of one or more exterior walls of a building. Such a model may include location points for such walls, as well as two-dimensional image data from such walls. When compared with complex three-dimensional point cloud models of objects, a two-dimensional façade model is much simpler. Processing an image to identify a match with a two-dimensional model of a wall also will generally consume fewer processing resources than processing one or more video images against a three-dimensional model of an object. Efficiencies in processor and memory systems are particularly important when working with mobile devices or wearable devices with significant limitations on resource availability.
Further still, by using global positioning systems or other location based systems to identify an initial rough location estimate, the processing resources needed to match two-dimensional façade data against a captured image may be further limited. Map databases may include image information and/or façade models for buildings in a particular location. Using such a database along with an initial rough location estimate may be used to limit the expected buildings in a captured image to a very small number, or may automatically be used to identify a single building. Starting with this information, some devices with limited processing resources can match the two-dimensional façade data against the captured image in a near real-time fashion. Some such devices may not be able to perform such near real-time calculations for three-dimensional matching. The perspective of a building that is represented in a captured image may then be used to create an accurate estimate of a position of the image sensor that was used to generate the captured image. Such an accurate position estimate may be used in a variety of ways, including use to properly place and track virtual objects within an environment as part of an augmented reality system.
As shown in
As shown in
The client devices 110 can execute conventional web browser applications or applications (also referred to as “apps”) that have been developed for a specific platform to include any of a wide variety of mobile computing devices and mobile-specific operating systems (e.g., IOS™, ANDROID™, WINDOWS® PHONE). In an example, the client devices 110 are executing the client applications 112. The client applications 112 can provide functionality to present information to a user 106 and communicate via the network 104 to exchange information with the social messaging system 130. Each of the client devices 110 can comprise a computing device that includes at least a display and communication capabilities with the network 104 to access the social messaging system 130. The client devices 110 comprise, but are not limited to, remote devices, work stations, computers, general purpose computers, Internet appliances, hand-held devices, wireless devices, portable devices, wearable computers, cellular or mobile phones, personal digital assistants (PDAs), automotive computing devices with driver heads up displays (HUD), smart phones, tablets, ultrabooks, netbooks, laptops, desktops, multi-processor systems, microprocessor-based or programmable consumer electronics, game consoles, set-top boxes, network personal computers (PCs), mini-computers, and the like. Users 106 can include a person, a machine, or other means of interacting with the client devices 110. In some embodiments, the users 106 interact with the social messaging system 130 via the client devices 110.
As shown in
An individual can register with the social messaging system 130 to become a member of the social messaging system 130. Once registered, a member can form social network relationships (e.g., friends, followers, or contacts) on the social messaging system 130 and interact with a broad range of applications provided by the social messaging system 130.
The application logic layer 126 includes various application logic modules 150, which, in conjunction with the interface modules 140, generate various user interfaces with data retrieved from various data sources or data services in the data layer 128. Individual application logic modules 150 may be used to implement the functionality associated with various applications, services, and features of the social messaging system 130, including aspects of augmented reality system 160. For instance, a social messaging application can be implemented with one or more of the application logic modules 150. The social messaging application provides a messaging mechanism for users of the client devices 110 to send and receive messages that include text and media content such as pictures and video. The social messaging application may also include mechanisms for providing augmented reality displays and content that integrate pictures and video with virtual objects. The client devices 110 may provide augmented reality displays and may also enable users to access and view the messages from the social messaging application for a specified period of time (e.g., limited or unlimited). In an example, a particular message is accessible to a message recipient for a predefined duration (e.g., specified by a message sender) that begins when the particular message is first accessed. After the predefined duration elapses, the message is deleted and is no longer accessible to the message recipient. Similarly, augmented reality content may be provided for a predefined duration. Other applications and services may be separately embodied in their own application logic modules 150.
As illustrated in
The communication module 210 provides various communication functionality. For example, the communication module 210 receives, accesses, or otherwise obtains image data of an image from a user device. In a specific example, the communication module 210 receives substantially real-time image data from a camera sensor of a smart phone (e.g., a single frame of image data or a continuous stream of frames captured by a camera sensor of the smart phone). The communication module 210 exchanges network communications with the database servers 132, the client devices 110, and the third party servers 120. The information retrieved by the communication module 210 includes data associated with the user (e.g., member profile data from an online account or social network service data) or other data to facilitate the functionality described herein.
The presentation module 220 provides various presentation and user interface functionality operable to interactively present and receive information to and from the user. For instance, the presentation module 220 is used to manage output of image data with aligned and inserted virtual objects, so that augmented reality images may be presented on a display. As mentioned above, these images may be presented in real-time or near real-time as the images are captured, processed to add virtual objects, and displayed with the virtual objects as quickly as possible. Presentation module 220 is also utilizable to present user interfaces, AR objects, or any such information generated in response to decoding an optical barcode such as optical barcode 806 discussed below. In various embodiments, the presentation module 220 presents or causes presentation of additional information (e.g., visually displaying information on a screen, acoustic output, haptic feedback). The process of interactively presenting information is intended to include the exchange of information between a particular device and the user. The user may provide input to interact with the user interface in many possible manners, such as alphanumeric, point based (e.g., cursor), tactile, or other input (e.g., touch screen, tactile sensor, light sensor, infrared sensor, biometric sensor, microphone, gyroscope, accelerometer, or other sensors). The presentation module 220 provides many other user interfaces to facilitate functionality described herein. The term “presenting” as used herein is intended to include communicating information or instructions to a particular device that is operable to perform presentation based on the communicated information or instructions. This may include both output on a screen as well as projection of an image onto a user's eye.
The configuration module 230 may be used to accept and manage user selection of system options. This may include options to select various augmented reality selections, including enabling augmented reality and requesting certain types of augmented reality information to be provided or triggered based on user inputs or input based triggers. For example, configuration module 230 may include a setting provided by a user to automatically present information about certain types of locations when the locations are identified in an image based location system or a map positioning system. Configuration module 230 may also accept user settings to automatically provide direction information in an augmented reality image when direction input triggers are received via communication module 210. In other embodiments, any other triggers for implementing image based location or augmented reality images may be managed by configuration module 230. For example, the configuration module 230 extracts and analyzes candidate shape features or candidate contour characteristics from image data of the image received from the user device (e.g., the client devices 110) when a system includes such analysis as a trigger for display of augmented reality images. The configuration module 230 determines satisfaction of various rules or criteria associated with the extracted candidate shape features. The configuration module 230 compares the extracted candidate shape features with reference shape features of the custom graphic or another reference image. The configuration module 230 can employ a wide variety of schemes and techniques to extract candidate shape features from the image data of the image and subsequently trigger display of augmented reality images.
The alignment module 240 provides image processing functionality to determine and verify an alignment of the image data captured by an image sensor and the virtual objects placed into the image. In some embodiments, alignment module 240 may access or generate a computer model of the environment, and may use the computer model to insert virtual items into an image based on the computer model of the environment. In some embodiments, alignment module 240 may perform threshold or rule checks to verify that virtual items displayed in augmented reality images meet certain quality metrics to provide an acceptable user experience. This may include verifying that a virtual object does not move in unexpected ways with respect to objects in an image, that images captured by an image sensor are sufficiently stable over time to enable augmented reality functions, or other such metrics. In some embodiments, the alignment module 240 extracts spatial attributes from the image data. In various embodiments, the spatial attributes include at least one of position, orientation, scale, or other spatial aspects of objects in images. The alignment module 240 determines an alignment of the image objects based on the spatial attributes (e.g., a particular orientation). In an example, the alignment module 240 can determine an alignment including position and orientation based on the spatial attributes and generate a transformed image according to the alignment.
The virtual item module 250 provides functionality to generate images associated with virtual items. In some embodiments, this may include graphics information related to virtual location markers, virtual direction arrows, or virtual items or objects. In some embodiments, this may include graphics information for inserting mobile virtual objects into video (e.g., virtual animals, robots, dinosaurs, video display, etc.). In some embodiments, for each virtual object, presentation rules may be stored in virtual item module 250 and used by other modules to verify that virtual objects may be inserted into image data with sufficient output quality.
The analysis module 260 provides functionality to perform a variety of image processing operations. Such operations may include image processing operations to identify key points in an image and to match two-dimensional façade data against portions of an image to identify a match. For example, in some embodiments, analysis module 260 may accept an image and identify building corners or other key points in the image that may contain two-dimensional pattern data as part of a façade. Analysis module 260 may then take façade data from a model and match the portion of the image to a building façade model included in the façade data. In some embodiments, if no match is found, an analysis module 260 operating on a client device 110 may request additional information or additional processing by an analysis module 260 operating on a remote server, such as a third party server 120 or a server that is part of a social messaging system 130.
The map positioning system 270 provides map data including associations between map locations and façade data associated with buildings in a location, or any other such information in a system. Map positioning system 270 may also interface with remote servers or systems, which may provide this information. Additional aspects of a map positioning system 270 are discussed below with respect to
Image based location system 161 may comprise modules to accept street view images from any number of sources and analyze the images to generate façade data. Such façade data may include two-dimensional estimates of certain patterns on a building, as well as key point information for simple building locations, such as the locations of building corners or corners of two-dimensional façade patterns on a building. In some embodiments, information from multiple images may be used to generate façade data for a single building. Such information from multiple images may be used to match colors in different lighting situations, or to match minor changes over time to a building façade. In some embodiments, specialized image and location capture equipment may be used to generate information about building locations, keypoints of buildings, and building façade data with high accuracy in order to build a database of outdoor images of buildings in order to provide accurate references for image based location systems. Capturing locations of building corners, for example, with high accuracy (e.g., accuracy on the order of single digit centimeters or millimeters) provides a basis for an image based location estimate for a camera position with similar errors. In some embodiments, determining a camera position within a few centimeters (e.g., 5 cm) is sufficient to provide augmented reality presentation with a low chance of clear errors in the output images that break the reality illusion of augmented reality images.
In some embodiments, image based location system 161 may be distributed over a local client device and a remote server, with low information façade models (e.g., models with low-resolution and/or low color two-dimensional façade data and a small number of keypoints) stored locally on a device for regularly visited locations, expected future travel locations, or for buildings which the system believes might be near a device in the future. High information models (e.g., high resolution, high color information, and/or high numbers of three-dimensional keypoints) may be stored remotely and used when local compact façade models fail. Image based location system 161 may manage application of façade data and models to match portions of captured images using analysis module 260. Once a match is found using analysis module 260, location information related to a building matching façade data or keypoints in a building may be used to calculate a relative position of the camera perspective in a captured image. This relative position may be used to determine an absolute position based on the position of building keypoints or other absolute position information that is part of a façade or other model for a building associated with façade data.
Further still, in some embodiments, the calculations performed to match façade data from a database to a portion of an image may also be used to generate two dimensional augmented reality objects that match the façade surface.
In some such embodiments, an AR sticker object may be attached to a building with associated façade data in an augmented reality system. AR façade sticker object 394 is an emoji graphic used as an augmented reality object in image 301. As a perspective of an augmented reality view changes, the perspective of AR façade sticker object 394 changes to maintain the appearance that AR façade sticker object 394 is attached to the building wall. In order to eliminate redundant calculations, the perspective data about first structure façade portion 360 may be used to calculate the perspective required for AR façade sticker object 394, since they are in the same plane of the augmented reality space.
In other embodiments, AR objects such as AR object 392 may be 3D objects, such that an AR object like AR object 392 could be a sphere with a face on one side. Another such AR object could be any such 3D version of an emoji, face, animal, or other object. In one embodiment, an AR object could be a 3D tree covered with colored lights in a varying pattern. Any such AR object may also include animations. For example, the lights on the tree could sparkle and blink in different patterns. Such an AR object could further be placed or move, such that the tree with blinking lights could spin while moving through the air. In some embodiments, the system is able to generate and place an associated “sticker” version of such a 3D AR object. This may be done with a 2D projection of the 3D object at a user viewing elevation or a system standard (e.g. 0, 15 degree, etcetera) elevation. Such a generated 2D sticker object can then be placed on a wall or façade using the calculations previously performed by the system as described within the context of various other embodiments herein. If multiple 2D sticker objects are generated from different viewing angles, the stickers may have different patterns due to the different viewpoints. The 2D sticker versions may have fixed coloring, or may maintain some of the animations of the 3D object. For example, the lights on a 2D tree may sparkle and blink similar to those in the corresponding 3D AR object. Thus, as described herein, AR objects may include a variety of faces, emoji, animals, custom user made objects, or any other such possible AR objects. Such AR objects may have associated animations, sounds, transformations, and any other such AR object functionality.
Some embodiments described herein can then use communication data or a set of pictogram data stored at the device to generate augmented reality images with these sticker objects. One embodiment involves receiving or accessing at the device, two-dimensional augmented reality data for a sticker object, determining an augmented realty placement of the sticker object as positioned on a plane with the one or more façade surface locations, using the expected perspective for the low-resolution two-dimensional façade pattern as a sticker object perspective, and generating an augmented reality image comprising the sticker object on the plane with the one or more façade surface locations based on the expected perspective.
The two-dimensional augmented reality data can, in some embodiments, represent an emoji object selected by a user input from a set of augmented reality system pictograms. A user interface within a messaging or augmented reality system may display a set of pictograms or emoji images on an interface similar to the interface of
Even with the limitations of two-dimensional façade matching, comparing façade data for many buildings against multiple facades within an image is a processor intensive process. Thus, as described above, an initial location estimate may limit the number of matching procedures needed. A GPS, network assisted location system, or other device sensors and systems for location determination may thus be used to provide an initial location estimate. Such estimates may have errors of a few meters or tens of meters.
As illustrated by
In
In the diagram 800, a scene 802 illustrates a façade 804 that includes an optical barcode 806, and a user 810. It will be appreciated that the optical barcode 806 can be displayed in a variety of manners such as on a user device display, a computer display, woven or otherwise affixed to an article of clothing or another product, or included in a variety of printed items.
In an example embodiment, the user device 814 captures an image of the poster 804 that includes the optical barcode 806. The augmented reality system 160 receives the image data representing the image from the user device 814. In this example embodiment, the augmented reality system 160 is included in the user device 814 (e.g., an application executing on a smart phone of the user 810), although in other example embodiments, the augmented reality system 160 can reside on a server (e.g., a server of the social messaging system 130) that is communicatively coupled with the user device 814. The captured image may then be compared with façade data about poster 804 to identify a position of an image sensor. This image sensor position may then be used to provide accurate placement of virtual objects in an AR scene.
Operation 902 involves determining, using a first positioning system, a first position estimate for the device. Such a position system may include any combination of a GPS, a network assisted location system such as a secure user plane location (SUPL) system, position systems based on sensors of a device such as accelerometer or gyroscope tracking systems, or any other such initial tracking method.
Then, based on the first position estimate, operation 904 involves accessing a set of structure facade data describing one or more structure facades associated with the first position estimate. As described above, in some embodiments, a database of street images and façade data may be generated using specialized equipment. In other embodiments, large amounts of user data may be used to gather images and many data points regarding façade data and building key points. The façade data may include different types and combinations of data. In some embodiments, façade data includes absolute location information for one or more points on the façade that are clearly identifiable. Such points include building corners or clearly defined patterns or image corners. Façade data may additionally include two-dimensional image patterns that are part of a building façade, such as data versions of artwork, signage, logos, words, windows, arches, doorways, or other sufficiently two-dimensional portions of a building side.
In some embodiments, images captured for use with augmented reality systems may be provided as feedback to generate and update façade data while a user is using the system. In order to provide privacy in such situations, in some embodiments, the image data captured by users may be processed to eliminate or blur users, or may have all data below user height level removed with only building or façade portions of images transferred to a server system for use in generating or updating façade data using map, building, or environment models.
Operation 906 then involves capturing, by an image sensor of the device, a first image of an environment. Such an image sensor may be any camera device sensor or light sensor capable of capturing two-dimensional information of a building and an environment. In some embodiments, additional sensors may be present including multiple image sensors or sensors for capturing three-dimensional data. Such embodiments may supplement the two-dimensional analysis of façade data matched to façade portions of images as allowed by system resource limitations such as battery and processing power limitations.
Then, at operation 908, using the set of structure facade data, a first structure facade portion of the first image of the environment is identified, wherein the first structure façade portion matches first structure façade data of the set of structure façade data. Operation 910 then involves calculating, based at least in part on the first structure façade portion of the first image of the environment, a second position estimate of the device.
In various embodiments, the image data from the user device is received in response to a user-initiated image capture, a periodic monitoring of image data being detected by the optical sensor of the user device, or a combination thereof. In some embodiments, the image data represents an image or video being captured by the user device in substantially real-time (e.g., a live image feed from a camera sensor of a smart phone). In some embodiments, elements of captured images may be used to initiate generation of AR images, and an output of video enhanced with AR elements, which also attempts to output the AR images as video in substantially real-time. In embodiments where the image data comprises video image data, the augmented reality system 160 can analyze individual frames of the video or a combination of multiple frames of the video to detect and decode trigger elements or matched façade portions of images.
The matching portion of method 900 may use various techniques for matching façade data with an image. In some embodiments, combinations of edge detection in images may be compared against edges identified in façade data. In other embodiments, candidate shapes for each building façade may be present in façade data and compared against image data. Some embodiments identify shape features such as contour lines or localized concentrations of color or shading of the image. In some embodiments, a matching system extracts multiple candidate shape features from the image data. In some embodiments, the candidate shape feature includes various shape feature data such as a position of the candidate shape feature relative to a boundary of the image, a brightness of the candidate shape feature relative to the image, an average color of the candidate shape feature, and so forth. Limitation of the match to two-dimensional façade data as described above increases match performance while limiting resource usage as described above when compared to three-dimensional match processes.
In further example embodiments, façade data stored locally on a mobile device includes a low-resolution copy of the image. A matching resolution version of the captured image is created. Various image processing may be performed, such as a blur (e.g., a Gaussian blur function or another blur function) and a thresholding, to generate a modified low-resolution image. The thresholding image process can include adjusting lighter colors (e.g., as determined by a threshold or threshold range) of the low-resolution copy of the image to a white color and darker colors (e.g., as determined by a threshold or threshold range) of the low-resolution copy of the image to a black color. Façade data may then be compared against a standardized image. In other embodiments, façade data may include matching data customized for environmental factors present at the time an image is taken, such as sun position, cloud impact on an image, or other environmental factors.
In some embodiments, matching as described in operation 908 may be performed through determining that a candidate portion of an image satisfies one or more shape feature criteria or rules associated with façade data.
In some embodiments, the matching system can perform an image transform using the spatial attributes (e.g., a de-skew, a rotation, a scale, or another type of image transform) to improve detectability or readability of data encoded in a portion of the image. The particular image transforms used to identify a match may further be used as part of the calculation of the second position estimate of the device in operation 910. In some embodiments, an initial set of match calculations are performed in an operation 908, and once a threshold match is completed, subsequent calculations are performed to further limit error in the second position estimate by using additional refinements of image transforms including finer transform adjustments and match verification.
As described above with respect to
Such an embodiment may involve calculating, from the first position estimate and the one or more façade surface locations, an expected perspective for the low-resolution two-dimensional façade pattern and processing the low-resolution two-dimensional façade pattern to generate a first perspective pattern. A determination may then be made at the mobile device that the first perspective pattern does not meet a threshold match level for the first image. A supplemental set of façade data may then be requested from a first server computer. This may be a third party resource requested to provide additional detailed information or analysis, or may be a server of a system operating a portion of an augmented reality or image based matching system as described in
In some embodiments, particularly embodiments using remote resources via a network, a delay may occur between matching of the image to façade data and a current time or a most recently captured image for a near real-time augmented reality video or display. In such embodiments, a system may track relative changes in movement of a device over time, and may use the image based location to improve later sensor position estimates. This may be done by keeping a record of video frames and images or other sensor data and calculating forward a position from the image based estimate using any available data. In some embodiments, an initial resource intensive matching may be performed remotely, with subsequent matching and sensor location estimates performed locally using lower resource matching and estimation processes. In some such embodiments, errors may be tracked, and remote resources used periodically to update position estimates and reduce errors that may grow over time in calculations on a local mobile device.
Any above method may be repeated over time to further improve a position estimate, with any number of subsequent estimates based on both a first image and subsequent images matched against façade data.
Further, as described above, in some such embodiments, images may be captured by a first device, such as a wearable device, and local estimates performed on a paired device such as a smartphone. Such systems may also use remote server resources as described above.
Many varieties of applications (also referred to as “apps”) can be executed on the mobile device 1000, such as native applications (e.g., applications programmed in Objective-C, Swift, or another suitable language running on IOS™ or applications programmed in Java running on ANDROID™), mobile web applications (e.g., applications written in Hypertext Markup Language-5 (HTML5)), or hybrid applications (e.g., a native shell application that launches an HTML5 session). For example, the mobile device 1000 includes a messaging app, an audio recording app, a camera app, a book reader app, a media app, a fitness app, a file management app, a location app, a browser app, a settings app, a contacts app, a telephone call app, or other apps (e.g., gaming apps, social networking apps, biometric monitoring apps). In another example, the mobile device 1000 includes a social messaging app 1008 such as SNAPCHAT® that, consistent with some embodiments, allows users to exchange ephemeral messages that include media content. In this example, the social messaging app 1008 can incorporate aspects of embodiments described herein.
Certain embodiments are described herein as including logic or a number of components, modules, or mechanisms. Modules can constitute either software modules (e.g., code embodied on a machine-readable medium) or hardware modules. A “hardware module” is a tangible unit capable of performing certain operations and can be configured or arranged in a certain physical manner. In various example embodiments, one or more computer systems (e.g., a standalone computer system, a client computer system, or a server computer system) or one or more hardware modules of a computer system (e.g., a processor or a group of processors) can be configured by software (e.g., an application or application portion) as a hardware module that operates to perform certain operations as described herein.
In some embodiments, a hardware module can be implemented mechanically, electronically, or any suitable combination thereof. For example, a hardware module can include dedicated circuitry or logic that is permanently configured to perform certain operations. For example, a hardware module can be a special-purpose processor, such as a Field-Programmable Gate Array (FPGA) or an Application Specific Integrated Circuit (ASIC). A hardware module may also include programmable logic or circuitry that is temporarily configured by software to perform certain operations. For example, a hardware module can include software executed by a general-purpose processor or other programmable processor. Once configured by such software, hardware modules become specific machines (or specific components of a machine) uniquely tailored to perform the configured functions and are no longer general-purpose processors. It will be appreciated that the decision to implement a hardware module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) can be driven by cost and time considerations.
Accordingly, the phrase “hardware module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired), or temporarily configured (e.g., programmed) to operate in a certain manner or to perform certain operations described herein. As used herein, “hardware-implemented module” refers to a hardware module. Considering embodiments in which hardware modules are temporarily configured (e.g., programmed), each of the hardware modules need not be configured or instantiated at any one instance in time. For example, where a hardware module comprises a general-purpose processor configured by software to become a special-purpose processor, the general-purpose processor may be configured as respectively different special-purpose processors (e.g., comprising different hardware modules) at different times. Software accordingly configures a particular processor or processors, for example, to constitute a particular hardware module at one instance of time and to constitute a different hardware module at a different instance of time.
Hardware modules can provide information to, and receive information from, other hardware modules. Accordingly, the described hardware modules can be regarded as being communicatively coupled. Where multiple hardware modules exist contemporaneously, communications can be achieved through signal transmission (e.g., over appropriate circuits and buses) between or among two or more of the hardware modules. In embodiments in which multiple hardware modules are configured or instantiated at different times, communications between such hardware modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware modules have access. For example, one hardware module can perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware module can then, at a later time, access the memory device to retrieve and process the stored output. Hardware modules can also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information).
The various operations of example methods described herein can be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors constitute processor-implemented modules that operate to perform one or more operations or functions described herein. As used herein, “processor-implemented module” refers to a hardware module implemented using one or more processors.
Similarly, the methods described herein can be at least partially processor-implemented, with a particular processor or processors being an example of hardware. For example, at least some of the operations of a method can be performed by one or more processors or processor-implemented modules. Moreover, the one or more processors may also operate to support performance of the relevant operations in a “cloud computing” environment or as a “software as a service” (SaaS). For example, at least some of the operations may be performed by a group of computers (as examples of machines including processors), with these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., an API).
The performance of certain of the operations may be distributed among the processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processors or processor-implemented modules can be located in a single geographic location (e.g., within a home environment, an office environment, or a server farm). In other example embodiments, the processors or processor-implemented modules are distributed across a number of geographic locations.
The modules, methods, applications and so forth described in conjunction with the figures above are implemented in some embodiments in the context of a machine and an associated software architecture. The sections below describe representative software architecture(s) and machine (e.g., hardware) architecture that are suitable for use with the disclosed embodiments.
Software architectures are used in conjunction with hardware architectures to create devices and machines tailored to particular purposes. For example, a particular hardware architecture coupled with a particular software architecture will create a mobile device, such as a mobile phone, tablet device, or so forth. A slightly different hardware and software architecture may yield a smart device for use in the “internet of things.” While yet another combination produces a server computer for use within a cloud computing architecture. Not all combinations of such software and hardware architectures are presented here as those of skill in the art can readily understand how to implement the invention in different contexts from the disclosure contained herein.
Frame 32 additionally includes a left arm or temple piece 46 and a second arm or temple piece 47 coupled to the respective left and right end portions 41, 42 of the front piece 33 by any suitable means such as a hinge (not shown), so as to be coupled to the front piece 33, or rigidly or fixably secured to the front piece so as to be integral with the front piece 33. Each of the temple pieces 46 and 47 can include a first portion 51 that is coupled to the respective end portion 41 or 42 of the front piece 33 and any suitable second portion 52, such as a curved or arcuate piece, for coupling to the ear of the user. In one embodiment, the front piece 33 can be formed from a single piece of material, so as to have a unitary or integral construction.
Glasses 31 can include a computing device, such as computer 61, which can be of any suitable type so as to be carried by the frame 32 and, in one embodiment of a suitable size and shape, so as to be at least partially disposed in one of the temple pieces 46 and 47. In one embodiment, as illustrated in
The computer 61 additionally includes a battery 62 or other suitable portable power supply. In one embodiment, the battery 62 is disposed in one of the temple pieces 46 or 47. In the glasses 31 shown in
Glasses 31 include cameras 69. Although two cameras are depicted, other embodiments contemplate the use of a single or additional (i.e., more than two) cameras. In various embodiments, glasses 31 may include any number of input sensors or peripheral devices in addition to cameras 69. Front piece 33 is provided with an outward facing, forward-facing, or front or outer surface 66 that faces forward or away from the user when the glasses 31 are mounted on the face of the user, and an opposite inward-facing, rearward-facing, or rear or inner surface 67 that faces the face of the user when the glasses 31 are mounted on the face of the user. Such sensors can include inwardly-facing video sensors or digital imaging modules such as cameras that can be mounted on or provided within the inner surface 67 of the front piece 33 or elsewhere on the frame 32 so as to be facing the user, and outwardly-facing video sensors or digital imaging modules such as cameras 69 that can be mounted on or provided with the outer surface 66 of the front piece 33 or elsewhere on the frame 32 so as to be facing away from the user. Such sensors, peripheral devices, or peripherals can additionally include biometric sensors, location sensors, or any other such sensors. In additional embodiments, similar elements may be presented as visors, within helmet or google based systems, in vehicle HUD displays, or in any other such device.
In various implementations, the operating system 1204 manages hardware resources and provides common services. The operating system 1204 includes, for example, a kernel 1220, services 1222, and drivers 1224. The kernel 1220 acts as an abstraction layer between the hardware and the other software layers consistent with some embodiments. For example, the kernel 1220 provides memory management, processor management (e.g., scheduling), component management, networking, and security settings, among other functionality. The services 1222 can provide other common services for the other software layers. The drivers 1224 are responsible for controlling or interfacing with the underlying hardware, according to some embodiments. For instance, the drivers 1224 can include display drivers, camera drivers, BLUETOOTH® drivers, flash memory drivers, serial communication drivers (e.g., Universal Serial Bus (USB) drivers), WI-FI® drivers, audio drivers, power management drivers, and so forth.
In some embodiments, the libraries 1206 provide a low-level common infrastructure utilized by the applications 1210. The libraries 1206 can include system libraries 1230 (e.g., C standard library) that can provide functions such as memory allocation functions, string manipulation functions, mathematic functions, and the like. In addition, the libraries 1206 can include API libraries 1232 such as media libraries (e.g., libraries to support presentation and manipulation of various media formats such as Moving Picture Experts Group-4 (MPEG4), Advanced Video Coding (H.264 or AVC), Moving Picture Experts Group Layer-3 (MP3), Advanced Audio Coding (AAC), Adaptive Multi-Rate (AMR) audio codec, Joint Photographic Experts Group (JPEG or JPG), or Portable Network Graphics (PNG)), graphics libraries (e.g., an OpenGL framework used to render in two dimensions (2D) and three dimensions (3D) in a graphic content on a display), database libraries (e.g., SQLite to provide various relational database functions), web libraries (e.g., WebKit to provide web browsing functionality), and the like. The libraries 1206 can also include a wide variety of other libraries 1234 to provide many other APIs to the applications 1210.
The frameworks 1208 provide a high-level common infrastructure that can be utilized by the applications 1210, according to some embodiments. For example, the frameworks 1208 provide various graphic user interface (GUI) functions, high-level resource management, high-level location services, and so forth. The frameworks 1208 can provide a broad spectrum of other APIs that can be utilized by the applications 1210, some of which may be specific to a particular operating system 1204 or platform.
In an example embodiment, the applications 1210 include a home application 1250, a contacts application 1252, a browser application 1254, a book reader application 1256, a location application 1258, a media application 1260, a messaging application 1262, a game application 1264, and a broad assortment of other applications such as a third party application 1266. According to some embodiments, the applications 1210 are programs that execute functions defined in the programs. Various programming languages can be employed to create one or more of the applications 1210, structured in a variety of manners, such as object-oriented programming languages (e.g., Objective-C, Java, or C++) or procedural programming languages (e.g., C or assembly language). In a specific example, the third party application 1266 (e.g., an application developed using the ANDROID™ or IOS™ software development kit (SDK) by an entity other than the vendor of the particular platform) may be mobile software running on a mobile operating system such as IOS™, ANDROID™, WINDOWS® Phone, or another mobile operating systems. In this example, the third party application 1266 can invoke the API calls 1212 provided by the operating system 1204 to facilitate functionality described herein.
An augmented reality application 1267 may implement any system or method described herein, including accessing map information, processing image an façade data matching, or any other operation described herein. Further, in some embodiments, messaging application 1262 and augmented reality application 1267 may operate together as part of an ephemeral messaging application. Such an ephemeral messaging application may operate to generate images, allow users to add augmented reality elements to the images, and communicate some or all of the images and/or augmented reality data to another system user. After a deletion trigger has been met, the sent data is communicated from the receiving user's system, and may also be synchronized to delete the images and/or augmented reality data from any server involved in communication of the ephemeral message that included the image and/or the augmented reality data. In some embodiments, the trigger for deletion of data from a receiving user's device may be a timer that indicates how long an augmented reality image is displayed for. In other embodiments, the ephemeral messaging system may have set date and time triggers for deletion, or deletion associated with a number of times that a receiving user has accessed the data.
For example, in one embodiment, a user may send a set of augmented reality data to another user via an ephemeral messaging system. The ephemeral messaging data may include an emoji sticker object attached to a geolocation. When a receiving user's device receives the ephemeral message, the emoji will be available for viewing within an augmented reality system with limitations set by the ephemeral messaging system. After a limitation trigger has been met, the emoji sticker will no longer be available for viewing. In other embodiments, a user may select an ephemeral or non-ephemeral status for such a message including augmented reality data, such that a non-ephemeral message including the data will wait for a selection from a receiving user to delete the augmented reality data, and the augmented reality data that is part of the message may be stored on a communication server indefinitely.
The machine 1300 can include processors 1310, memory/storage 1330, and I/O components 1350, which can be configured to communicate with each other such as via a bus 1302. In an example embodiment, the processors 1310 (e.g., a Central Processing Unit (CPU), a Reduced Instruction Set Computing (RISC) processor, a Complex Instruction Set Computing (CISC) processor, a Graphics Processing Unit (GPU), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Radio-Frequency Integrated Circuit (RFIC), another processor, or any suitable combination thereof) can include, for example, processor 1312 and processor 1314 that may execute instructions 1316. The term “processor” is intended to include multi-core processor that may comprise two or more independent processors (sometimes referred to as “cores”) that can execute instructions contemporaneously. Although
The memory/storage 1330 can include a main memory 1332, a static memory 1334, or other memory storage, and a storage unit 1336, both accessible to the processors 1310 such as via the bus 1302. The storage unit 1336 and memory 1332 store the instructions 1316 embodying any one or more of the methodologies or functions described herein. The instructions 1316 can also reside, completely or partially, within the memory 1332, within the storage unit 1336, within at least one of the processors 1310 (e.g., within the processor's cache memory), or any suitable combination thereof, during execution thereof by the machine 1300. Accordingly, the memory 1332, the storage unit 1336, and the memory of the processors 1310 are examples of machine-readable media.
As used herein, the term “machine-readable medium” means a device able to store instructions and data temporarily or permanently and may include, but is not be limited to, random-access memory (RAM), read-only memory (ROM), buffer memory, flash memory, optical media, magnetic media, cache memory, other types of storage (e.g., Erasable Programmable Read-Only Memory (EEPROM)) or any suitable combination thereof. The term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, or associated caches and servers) able to store instructions 1316. The term “machine-readable medium” shall also be taken to include any medium, or combination of multiple media, that is capable of storing instructions (e.g., instructions 1316) for execution by a machine (e.g., machine 1300), such that the instructions, when executed by one or more processors of the machine 1300 (e.g., processors 1310), cause the machine 1300 to perform any one or more of the methodologies described herein. Accordingly, a “machine-readable medium” refers to a single storage apparatus or device, as well as “cloud-based” storage systems or storage networks that include multiple storage apparatus or devices. The term “machine-readable medium” excludes signals per se.
The I/O components 1350 can include a wide variety of components to receive input, provide output, produce output, transmit information, exchange information, capture measurements, and so on. The specific I/O components 1350 that are included in a particular machine will depend on the type of machine. For example, portable machines such as mobile phones will likely include a touch input device or other such input mechanisms, while a headless server machine will likely not include such a touch input device. It will be appreciated that the I/O components 1350 can include many other components that are not shown in
In further example embodiments, the I/O components 1350 can include biometric components 1356, motion components 1358, environmental components 1360, or position components 1362 among a wide array of other components. For example, the biometric components 1356 can include components to detect expressions (e.g., hand expressions, facial expressions, vocal expressions, body gestures, or eye tracking), measure biosignals (e.g., blood pressure, heart rate, body temperature, perspiration, or brain waves), identify a person (e.g., voice identification, retinal identification, facial identification, fingerprint identification, or electroencephalogram based identification), and the like. The motion components 1358 can include acceleration sensor components (e.g., an accelerometer), gravitation sensor components, rotation sensor components (e.g., a gyroscope), and so forth. The environmental components 1360 can include, for example, illumination sensor components (e.g., a photometer), temperature sensor components (e.g., one or more thermometers that detect ambient temperature), humidity sensor components, pressure sensor components (e.g., a barometer), acoustic sensor components (e.g., one or more microphones that detect background noise), proximity sensor components (e.g., infrared sensors that detect nearby objects), gas sensor components (e.g., machine olfaction detection sensors, gas detection sensors to detect concentrations of hazardous gases for safety or to measure pollutants in the atmosphere), or other components that may provide indications, measurements, or signals corresponding to a surrounding physical environment. The position components 1362 can include location sensor components (e.g., a GPS receiver component), altitude sensor components (e.g., altimeters or barometers that detect air pressure from which altitude may be derived), orientation sensor components (e.g., magnetometers), and the like.
Communication can be implemented using a wide variety of technologies. The I/O components 1350 may include communication components 1364 operable to couple the machine 1300 to a network 1380 or devices 1370 via a coupling 1382 and a coupling 1372, respectively. For example, the communication components 1364 include a network interface component or other suitable device to interface with the network 1380. In further examples, communication components 1364 include wired communication components, wireless communication components, cellular communication components, Near Field Communication (NFC) components, BLUETOOTH® components (e.g., BLUETOOTH® Low Energy), WI-FI® components, and other communication components to provide communication via other modalities. The devices 1370 may be another machine or any of a wide variety of peripheral devices (e.g., a peripheral device coupled via a USB).
Moreover, the communication components 1364 can detect identifiers or include components operable to detect identifiers. For example, the communication components 1364 can include Radio Frequency Identification (RFID) tag reader components, NFC smart tag detection components, optical reader components (e.g., an optical sensor to detect one-dimensional bar codes such as a Universal Product Code (UPC) bar code, multi-dimensional bar codes such as a Quick Response (QR) code, Aztec Code, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code, Uniform Commercial Code Reduced Space Symbology (UCC RSS)-2D bar codes, and other optical codes), acoustic detection components (e.g., microphones to identify tagged audio signals), or any suitable combination thereof. In addition, a variety of information can be derived via the communication components 1364, such as location via Internet Protocol (IP) geo-location, location via WI-FI®) signal triangulation, location via detecting a BLUETOOTH® or NFC beacon signal that may indicate a particular location, and so forth.
In various example embodiments, one or more portions of the network 1380 can be an ad hoc network, an intranet, an extranet, a virtual private network (VPN), a local area network (LAN), a wireless LAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), a metropolitan area network (MAN), the Internet, a portion of the Internet, a portion of the Public Switched Telephone Network (PSTN), a plain old telephone service (POTS) network, a cellular telephone network, a wireless network, a WI-FI®) network, another type of network, or a combination of two or more such networks. For example, the network 1380 or a portion of the network 1380 may include a wireless or cellular network, and the coupling 1382 may be a Code Division Multiple Access (CDMA) connection, a Global System for Mobile communications (GSM) connection, or other type of cellular or wireless coupling. In this example, the coupling 1382 can implement any of a variety of types of data transfer technology, such as Single Carrier Radio Transmission Technology (1×RTT), Evolution-Data Optimized (EVDO) technology, General Packet Radio Service (GPRS) technology, Enhanced Data rates for GSM Evolution (EDGE) technology, third Generation Partnership Project (3GPP) including 3G, fourth generation wireless (4G) networks, Universal Mobile Telecommunications System (UMTS), High Speed Packet Access (HSPA), Worldwide Interoperability for Microwave Access (WiMAX), Long Term Evolution (LTE) standard, others defined by various standard setting organizations, other long range protocols, or other data transfer technology.
The instructions 1316 can be transmitted or received over the network 1380 using a transmission medium via a network interface device (e.g., a network interface component included in the communication components 1364) and utilizing any one of a number of well-known transfer protocols (e.g., HTTP). Similarly, the instructions 1316 can be transmitted or received using a transmission medium via the coupling 1372 (e.g., a peer-to-peer coupling) to devices 1370. The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding, or carrying the instructions 1316 for execution by the machine 1300, and includes digital or analog communications signals or other intangible medium to facilitate communication of such software.
Throughout this specification, plural instances may implement components, operations, or structures described as a single instance. Although individual operations of one or more methods are illustrated and described as separate operations, one or more of the individual operations may be performed concurrently, and nothing requires that the operations be performed in the order illustrated. Structures and functionality presented as separate components in example configurations may be implemented as a combined structure or component. Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements fall within the scope of the subject matter herein.
Although an overview of the inventive subject matter has been described with reference to specific example embodiments, various modifications and changes may be made to these embodiments without departing from the broader scope of embodiments of the present disclosure. Such embodiments of the inventive subject matter may be referred to herein, individually or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single disclosure or inventive concept if more than one is, in fact, disclosed.
The embodiments illustrated herein are described in sufficient detail to enable those skilled in the art to practice the teachings disclosed. Other embodiments may be used and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. The Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various embodiments is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled.
As used herein, the term “or” may be construed in either an inclusive or exclusive sense. Moreover, plural instances may be provided for resources, operations, or structures described herein as a single instance. Additionally, boundaries between various resources, operations, modules, engines, and data stores are somewhat arbitrary, and particular operations are illustrated in a context of specific illustrative configurations. Other allocations of functionality are envisioned and may fall within a scope of various embodiments of the present disclosure. In general, structures and functionality presented as separate resources in the example configurations may be implemented as a combined structure or resource. Similarly, structures and functionality presented as a single resource may be implemented as separate resources. These and other variations, modifications, additions, and improvements fall within a scope of embodiments of the present disclosure as represented by the appended claims. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense.
This application is a continuation of and claims the benefit of priority of U.S. patent application Ser. No. 16/913,503, filed Jun. 26, 2020, which application is a continuation of and claims the benefit of priority of U.S. patent application Ser. No. 16/438,226, filed Jun. 11, 2019, now issued as U.S. Pat. No. 10,733,802, which is a continuation of and claims the benefit of priority of U.S. patent application Ser. No. 16/136,849, filed Sep. 20, 2018, now issued as U.S. Pat. No. 10,366,543, which is a continuation of and claims the benefit of priority of U.S. patent application Ser. No. 15/830,965, filed Dec. 4, 2017, now issued as U.S. Pat. No. 10,102,680, which is a continuation of and claims the benefit of priority of U.S. patent application Ser. No. 15/591,887, filed on May 10, 2017, now issued as U.S. Pat. No. 9,836,890, which is a continuation of and claims the benefit of priority of U.S. patent application Ser. No. 14/954,090, filed Nov. 30, 2015, now issued as U.S. Pat. No. 9,652,896, which claims the benefit of priority to U.S. Provisional Patent Application No. 62/248,706, filed Oct. 30, 2015, each of which are hereby incorporated by reference herein in their entireties.
Number | Name | Date | Kind |
---|---|---|---|
666223 | Shedlock | Jan 1901 | A |
4581634 | Williams | Apr 1986 | A |
4975690 | Torres | Dec 1990 | A |
5072412 | Henderson, Jr. et al. | Dec 1991 | A |
5361205 | Nishino et al. | Nov 1994 | A |
5493692 | Theimer et al. | Feb 1996 | A |
5699444 | Palm | Dec 1997 | A |
5713073 | Warsta | Jan 1998 | A |
5754939 | Herz et al. | May 1998 | A |
5855008 | Goldhaber et al. | Dec 1998 | A |
5883639 | Walton et al. | Mar 1999 | A |
5999932 | Paul | Dec 1999 | A |
6009190 | Szeliski et al. | Dec 1999 | A |
6012098 | Bayeh et al. | Jan 2000 | A |
6014090 | Rosen et al. | Jan 2000 | A |
6029141 | Bezos et al. | Feb 2000 | A |
6038295 | Mattes | Mar 2000 | A |
6049711 | Yehezkel et al. | Apr 2000 | A |
6154764 | Nitta et al. | Nov 2000 | A |
6158044 | Tibbetts | Dec 2000 | A |
6167435 | Druckenmiller et al. | Dec 2000 | A |
6204840 | Petelycky et al. | Mar 2001 | B1 |
6205432 | Gabbard et al. | Mar 2001 | B1 |
6216141 | Straub et al. | Apr 2001 | B1 |
6285381 | Sawano et al. | Sep 2001 | B1 |
6285987 | Roth et al. | Sep 2001 | B1 |
6310694 | Okimoto et al. | Oct 2001 | B1 |
6317789 | Rakavy et al. | Nov 2001 | B1 |
6334149 | Davis, Jr. et al. | Dec 2001 | B1 |
6349203 | Asaoka et al. | Feb 2002 | B1 |
6353170 | Eyzaguirre et al. | Mar 2002 | B1 |
6446004 | Cao et al. | Sep 2002 | B1 |
6449657 | Stanbach et al. | Sep 2002 | B2 |
6456852 | Bar et al. | Sep 2002 | B2 |
6484196 | Maurille | Nov 2002 | B1 |
6487586 | Ogilvie | Nov 2002 | B2 |
6487601 | Hubacher et al. | Nov 2002 | B1 |
6523008 | Avrunin | Feb 2003 | B1 |
6525731 | Suits et al. | Feb 2003 | B1 |
6542749 | Tanaka et al. | Apr 2003 | B2 |
6549768 | Fraccaroli | Apr 2003 | B1 |
6618593 | Drutman | Sep 2003 | B1 |
6622174 | Ukita et al. | Sep 2003 | B1 |
6631463 | Floyd et al. | Oct 2003 | B1 |
6636247 | Hamzy et al. | Oct 2003 | B1 |
6636855 | Holloway et al. | Oct 2003 | B2 |
6643684 | Malkin et al. | Nov 2003 | B1 |
6658095 | Yoakum et al. | Dec 2003 | B1 |
6665531 | Soderbacka et al. | Dec 2003 | B1 |
6668173 | Greene | Dec 2003 | B2 |
6684238 | Dutta | Jan 2004 | B1 |
6684257 | Camut et al. | Jan 2004 | B1 |
6698020 | Zigmond et al. | Feb 2004 | B1 |
6700506 | Winkler | Mar 2004 | B1 |
6701347 | Ogilvie | Mar 2004 | B1 |
6711608 | Ogilvie | Mar 2004 | B1 |
6720860 | Narayanaswami | Apr 2004 | B1 |
6724403 | Santoro et al. | Apr 2004 | B1 |
6757713 | Ogilvie et al. | Jun 2004 | B1 |
6832222 | Zimowski | Dec 2004 | B1 |
6834195 | Brandenberg et al. | Dec 2004 | B2 |
6836792 | Chen | Dec 2004 | B1 |
6898626 | Ohashi | May 2005 | B2 |
6959324 | Kubik et al. | Oct 2005 | B1 |
6970088 | Kovach | Nov 2005 | B2 |
6970907 | Ullmann et al. | Nov 2005 | B1 |
6980909 | Root et al. | Dec 2005 | B2 |
6981040 | Konig et al. | Dec 2005 | B1 |
7020494 | Sprlestersbach et al. | Mar 2006 | B2 |
7027124 | Foote et al. | Apr 2006 | B2 |
7072963 | Anderson et al. | Jul 2006 | B2 |
7085571 | Kainan et al. | Aug 2006 | B2 |
7110744 | Freeny, Jr. | Sep 2006 | B2 |
7124164 | Chemtob | Oct 2006 | B1 |
7149893 | Leonard et al. | Dec 2006 | B1 |
7173651 | Knowles | Feb 2007 | B1 |
7188143 | Szeto | Mar 2007 | B2 |
7203380 | Chiu et al. | Apr 2007 | B2 |
7206568 | Sudit | Apr 2007 | B2 |
7227937 | Yoakum et al. | Jun 2007 | B1 |
7237002 | Estrada et al. | Jun 2007 | B1 |
7240089 | Boudreau | Jul 2007 | B2 |
7243163 | Friend | Jul 2007 | B1 |
7269426 | Kokkonen | Sep 2007 | B2 |
7278168 | Chaudhury et al. | Oct 2007 | B1 |
7280658 | Amini et al. | Oct 2007 | B2 |
7315823 | Brondrup | Jan 2008 | B2 |
7349768 | Bruce et al. | Mar 2008 | B2 |
7356564 | Hartselle et al. | Apr 2008 | B2 |
7376715 | Cunningham et al. | May 2008 | B2 |
7394345 | Ehlinger et al. | Jul 2008 | B1 |
7411493 | Smith | Aug 2008 | B2 |
7423580 | Markhovsky et al. | Sep 2008 | B2 |
7454442 | Cobleigh et al. | Nov 2008 | B2 |
7478402 | Christensen et al. | Jan 2009 | B2 |
7496347 | Puranik | Feb 2009 | B2 |
7508419 | Toyama et al. | Mar 2009 | B2 |
7512649 | Faybishenko et al. | Mar 2009 | B2 |
7519670 | Hagale et al. | Apr 2009 | B2 |
7535890 | Rojas | May 2009 | B2 |
7546554 | Chiu et al. | Jun 2009 | B2 |
7607096 | Oreizy et al. | Oct 2009 | B2 |
7639943 | Kalajan | Dec 2009 | B1 |
7650231 | Gadler | Jan 2010 | B2 |
7668537 | DeVries | Feb 2010 | B2 |
7703140 | Nath et al. | Apr 2010 | B2 |
7720554 | Dibernardo et al. | May 2010 | B2 |
7737965 | Alter et al. | Jun 2010 | B2 |
7770137 | Forbes et al. | Aug 2010 | B2 |
7778973 | Choi | Aug 2010 | B2 |
7779444 | Glad | Aug 2010 | B2 |
7787886 | Markhovsky et al. | Aug 2010 | B2 |
7796946 | Eisenbach | Sep 2010 | B2 |
7801954 | Cadiz et al. | Sep 2010 | B2 |
7856360 | Kramer et al. | Dec 2010 | B2 |
7912289 | Kansal et al. | Mar 2011 | B2 |
7912896 | Wolovitz et al. | Mar 2011 | B2 |
8001204 | Burtner et al. | Aug 2011 | B2 |
8032586 | Challenger et al. | Oct 2011 | B2 |
8082255 | Carlson, Jr. et al. | Dec 2011 | B1 |
8090351 | Klein | Jan 2012 | B2 |
8098904 | Ioffe et al. | Jan 2012 | B2 |
8099109 | Altman et al. | Jan 2012 | B2 |
8112716 | Kobayashi | Feb 2012 | B2 |
8131597 | Hudetz | Mar 2012 | B2 |
8135166 | Rhoads | Mar 2012 | B2 |
8136028 | Loeb et al. | Mar 2012 | B1 |
8146001 | Reese | Mar 2012 | B1 |
8161115 | Yamamoto | Apr 2012 | B2 |
8161417 | Lee | Apr 2012 | B1 |
8170957 | Richard | May 2012 | B2 |
8183997 | Wong et al. | May 2012 | B1 |
8195203 | Tseng | Jun 2012 | B1 |
8199747 | Rojas et al. | Jun 2012 | B2 |
8208943 | Petersen | Jun 2012 | B2 |
8214443 | Hamburg | Jul 2012 | B2 |
8230258 | Yamagami | Jul 2012 | B2 |
8234350 | Gu et al. | Jul 2012 | B1 |
8238947 | Lottin et al. | Aug 2012 | B2 |
8244593 | Klinger et al. | Aug 2012 | B2 |
8276092 | Narayanan et al. | Sep 2012 | B1 |
8279319 | Date | Oct 2012 | B2 |
8280406 | Ziskind et al. | Oct 2012 | B2 |
8285199 | Hsu et al. | Oct 2012 | B2 |
8287380 | Nguyen et al. | Oct 2012 | B2 |
8301159 | Hamynen et al. | Oct 2012 | B2 |
8306922 | Kunal et al. | Nov 2012 | B1 |
8312086 | Velusamy et al. | Nov 2012 | B2 |
8312097 | Siegel et al. | Nov 2012 | B1 |
8326315 | Phillips et al. | Dec 2012 | B2 |
8326327 | Hymel et al. | Dec 2012 | B2 |
8332475 | Rosen et al. | Dec 2012 | B2 |
8352546 | Dollard | Jan 2013 | B1 |
8379130 | Forutanpour et al. | Feb 2013 | B2 |
8385950 | Wagner et al. | Feb 2013 | B1 |
8402097 | Szeto | Mar 2013 | B2 |
8405773 | Hayashi et al. | Mar 2013 | B2 |
8418067 | Cheng et al. | Apr 2013 | B2 |
8423409 | Rao | Apr 2013 | B2 |
8471914 | Sakiyama et al. | Jun 2013 | B2 |
8472935 | Fujisaki | Jun 2013 | B1 |
8502903 | Kashitani | Aug 2013 | B2 |
8503782 | Vincent et al. | Aug 2013 | B2 |
8510383 | Hurley et al. | Aug 2013 | B2 |
8525825 | Zhu et al. | Sep 2013 | B2 |
8527345 | Rothschild et al. | Sep 2013 | B2 |
8554627 | Svendsen et al. | Oct 2013 | B2 |
8560612 | Kilmer et al. | Oct 2013 | B2 |
8564710 | Nonaka et al. | Oct 2013 | B2 |
8570907 | Garcia, Jr. et al. | Oct 2013 | B2 |
8594680 | Ledlie et al. | Nov 2013 | B2 |
8601380 | Vaittinen et al. | Dec 2013 | B2 |
8613089 | Holloway et al. | Dec 2013 | B1 |
8660358 | Bergboer et al. | Feb 2014 | B1 |
8660369 | Llano et al. | Feb 2014 | B2 |
8660793 | Ngo et al. | Feb 2014 | B2 |
8676623 | Gale et al. | Mar 2014 | B2 |
8682350 | Altman et al. | Mar 2014 | B2 |
8712776 | Bellegarda et al. | Apr 2014 | B2 |
8718333 | Wolf et al. | May 2014 | B2 |
8724622 | Rojas | May 2014 | B2 |
8732168 | Johnson | May 2014 | B2 |
8744523 | Fan et al. | Jun 2014 | B2 |
8745132 | Obradovich | Jun 2014 | B2 |
8761800 | Kuwahara | Jun 2014 | B2 |
8761811 | Alonzo | Jun 2014 | B2 |
8768876 | Shim et al. | Jul 2014 | B2 |
8775972 | Spiegel | Jul 2014 | B2 |
8788680 | Naik | Jul 2014 | B1 |
8790187 | Walker et al. | Jul 2014 | B2 |
8797415 | Arnold | Aug 2014 | B2 |
8798646 | Wang et al. | Aug 2014 | B1 |
8856349 | Jain et al. | Oct 2014 | B2 |
8874677 | Rosen et al. | Oct 2014 | B2 |
8886227 | Schmidt et al. | Nov 2014 | B2 |
8909679 | Root et al. | Dec 2014 | B2 |
8909714 | Agarwal et al. | Dec 2014 | B2 |
8909725 | Sehn | Dec 2014 | B1 |
8914752 | Spiegel | Dec 2014 | B1 |
8933966 | Oi et al. | Jan 2015 | B2 |
8965460 | Rao et al. | Feb 2015 | B1 |
8972174 | Jeung et al. | Mar 2015 | B2 |
8972357 | Shim et al. | Mar 2015 | B2 |
8995433 | Rojas | Mar 2015 | B2 |
9015285 | Ebsen et al. | Apr 2015 | B1 |
9020745 | Johnston et al. | Apr 2015 | B2 |
9031283 | Arth et al. | May 2015 | B2 |
9040574 | Wang et al. | May 2015 | B2 |
9055416 | Rosen et al. | Jun 2015 | B2 |
9058687 | Kruglick | Jun 2015 | B2 |
9083770 | Drose et al. | Jul 2015 | B1 |
9094137 | Sehn et al. | Jul 2015 | B1 |
9098926 | Quan et al. | Aug 2015 | B2 |
9100806 | Rosen et al. | Aug 2015 | B2 |
9100807 | Rosen et al. | Aug 2015 | B2 |
9113301 | Spiegel et al. | Aug 2015 | B1 |
9119027 | Sharon et al. | Aug 2015 | B2 |
9123074 | Jacobs et al. | Sep 2015 | B2 |
9129432 | Quan et al. | Sep 2015 | B2 |
9143382 | Bhogal et al. | Sep 2015 | B2 |
9143681 | Ebsen et al. | Sep 2015 | B1 |
9148424 | Yang | Sep 2015 | B1 |
9152477 | Campbell et al. | Oct 2015 | B1 |
9191776 | Root et al. | Nov 2015 | B2 |
9204252 | Root | Dec 2015 | B2 |
9225805 | Kujawa et al. | Dec 2015 | B2 |
9225897 | Sehn et al. | Dec 2015 | B1 |
9237202 | Sehn | Jan 2016 | B1 |
9240074 | Berkovich et al. | Jan 2016 | B2 |
9251144 | Du et al. | Feb 2016 | B2 |
9258459 | Hartley | Feb 2016 | B2 |
9264463 | Rubinstein et al. | Feb 2016 | B2 |
9276886 | Samaranayake | Mar 2016 | B1 |
9294425 | Son | Mar 2016 | B1 |
9317133 | Korah et al. | Apr 2016 | B2 |
9317921 | Chao et al. | Apr 2016 | B2 |
9344606 | Hartley et al. | May 2016 | B2 |
9355123 | Wnuk et al. | May 2016 | B2 |
9361283 | Jones et al. | Jun 2016 | B2 |
9385983 | Sehn | Jul 2016 | B1 |
9396354 | Murphy et al. | Jul 2016 | B1 |
9407712 | Sehn | Aug 2016 | B1 |
9407816 | Sehn | Aug 2016 | B1 |
9430783 | Sehn | Aug 2016 | B1 |
9439041 | Parvizi et al. | Sep 2016 | B2 |
9443227 | Evans et al. | Sep 2016 | B2 |
9450907 | Pridmore et al. | Sep 2016 | B2 |
9459778 | Hogeg et al. | Oct 2016 | B2 |
9465816 | Johnson et al. | Oct 2016 | B2 |
9477368 | Filip et al. | Oct 2016 | B1 |
9482882 | Hanover et al. | Nov 2016 | B1 |
9482883 | Meisenholder | Nov 2016 | B1 |
9489661 | Evans et al. | Nov 2016 | B2 |
9491134 | Rosen et al. | Nov 2016 | B2 |
9495783 | Samarasekera et al. | Nov 2016 | B1 |
9498720 | Geisner et al. | Nov 2016 | B2 |
9532171 | Allen et al. | Dec 2016 | B2 |
9537811 | Allen et al. | Jan 2017 | B2 |
9560006 | Prado et al. | Jan 2017 | B2 |
9628950 | Noeth et al. | Apr 2017 | B1 |
9652896 | Jurgenson et al. | May 2017 | B1 |
9659244 | Anderton et al. | May 2017 | B2 |
9693191 | Sehn | Jun 2017 | B2 |
9705831 | Spiegel | Jul 2017 | B2 |
9710821 | Heath | Jul 2017 | B2 |
9742713 | Spiegel et al. | Aug 2017 | B2 |
9761045 | Cote et al. | Sep 2017 | B1 |
9785796 | Murphy et al. | Oct 2017 | B1 |
9805020 | Gorman et al. | Oct 2017 | B2 |
9825898 | Sehn | Nov 2017 | B2 |
9836890 | Jurgenson | Dec 2017 | B2 |
9854219 | Sehn | Dec 2017 | B2 |
9922431 | Gray et al. | Mar 2018 | B2 |
9961520 | Brooks et al. | May 2018 | B2 |
9965895 | Gray | May 2018 | B1 |
9984499 | Jurgenson et al. | May 2018 | B1 |
10074381 | Cowburn | Sep 2018 | B1 |
10074981 | Faley et al. | Sep 2018 | B2 |
10102680 | Jurgenson | Oct 2018 | B2 |
10304237 | Sequeira et al. | May 2019 | B2 |
10319149 | Cowburn et al. | Jun 2019 | B1 |
10366543 | Jurgenson | Jul 2019 | B1 |
10387730 | Cowburn et al. | Aug 2019 | B1 |
10497158 | Jain et al. | Dec 2019 | B2 |
10592095 | Kasemset et al. | Mar 2020 | B2 |
10614828 | Cowburn et al. | Apr 2020 | B1 |
10657596 | Chavez et al. | May 2020 | B1 |
10657708 | Jurgenson et al. | May 2020 | B1 |
10733802 | Jurgenson et al. | Aug 2020 | B2 |
10740974 | Cowburn et al. | Aug 2020 | B1 |
10773802 | Finlay | Sep 2020 | B2 |
10997760 | Berger et al. | May 2021 | B2 |
10997783 | Jurgenson et al. | May 2021 | B2 |
11189299 | Cowburn et al. | Nov 2021 | B1 |
11195018 | Cowburn et al. | Dec 2021 | B1 |
11222325 | Van Os et al. | Jan 2022 | B2 |
11315331 | Jurgenson | Apr 2022 | B2 |
11348265 | Nielsen et al. | May 2022 | B1 |
11380051 | Jurgenson et al. | Jul 2022 | B2 |
11430091 | Mccormack et al. | Aug 2022 | B2 |
20020047868 | Miyazawa | Apr 2002 | A1 |
20020078456 | Hudson et al. | Jun 2002 | A1 |
20020087631 | Sharma | Jul 2002 | A1 |
20020097257 | Miller et al. | Jul 2002 | A1 |
20020122659 | Mcgrath et al. | Sep 2002 | A1 |
20020128047 | Gates | Sep 2002 | A1 |
20020144154 | Tomkow | Oct 2002 | A1 |
20030001846 | Davis et al. | Jan 2003 | A1 |
20030016247 | Lai et al. | Jan 2003 | A1 |
20030017823 | Mager et al. | Jan 2003 | A1 |
20030020623 | Cao et al. | Jan 2003 | A1 |
20030023874 | Prokupets et al. | Jan 2003 | A1 |
20030037124 | Yamaura et al. | Feb 2003 | A1 |
20030040899 | Ogilvie | Feb 2003 | A1 |
20030050785 | Friedrich et al. | Mar 2003 | A1 |
20030052925 | Daimon et al. | Mar 2003 | A1 |
20030101044 | Krasnov | May 2003 | A1 |
20030101230 | Benschoter et al. | May 2003 | A1 |
20030110503 | Perkes | Jun 2003 | A1 |
20030126215 | Udell | Jul 2003 | A1 |
20030133041 | Curtis et al. | Jul 2003 | A1 |
20030148773 | Spriestersbach et al. | Aug 2003 | A1 |
20030164856 | Prager et al. | Sep 2003 | A1 |
20030217106 | Adar et al. | Nov 2003 | A1 |
20030229607 | Zellweger et al. | Dec 2003 | A1 |
20040027371 | Jaeger | Feb 2004 | A1 |
20040064429 | Hirstius et al. | Apr 2004 | A1 |
20040078367 | Anderson et al. | Apr 2004 | A1 |
20040095357 | Oh et al. | May 2004 | A1 |
20040111467 | Willis | Jun 2004 | A1 |
20040158739 | Wakai et al. | Aug 2004 | A1 |
20040189465 | Capobianco et al. | Sep 2004 | A1 |
20040203959 | Coombes | Oct 2004 | A1 |
20040215625 | Svendsen et al. | Oct 2004 | A1 |
20040243531 | Dean | Dec 2004 | A1 |
20040243688 | Wugofskl | Dec 2004 | A1 |
20050021444 | Bauer et al. | Jan 2005 | A1 |
20050022211 | Veselov et al. | Jan 2005 | A1 |
20050048989 | Jung | Mar 2005 | A1 |
20050052339 | Sprague | Mar 2005 | A1 |
20050078804 | Yomoda | Apr 2005 | A1 |
20050097176 | Schatz et al. | May 2005 | A1 |
20050102381 | Jiang et al. | May 2005 | A1 |
20050104976 | Currans | May 2005 | A1 |
20050114783 | Szeto | May 2005 | A1 |
20050119936 | Buchanan et al. | Jun 2005 | A1 |
20050122405 | Voss et al. | Jun 2005 | A1 |
20050162523 | Darrell et al. | Jul 2005 | A1 |
20050193340 | Amburgey et al. | Sep 2005 | A1 |
20050193345 | Klassen et al. | Sep 2005 | A1 |
20050198128 | Anderson | Sep 2005 | A1 |
20050223066 | Buchheit et al. | Oct 2005 | A1 |
20050288954 | McCarthy et al. | Dec 2005 | A1 |
20060001758 | Nam et al. | Jan 2006 | A1 |
20060026067 | Nicholas et al. | Feb 2006 | A1 |
20060107297 | Toyama et al. | May 2006 | A1 |
20060114338 | Rothschild | Jun 2006 | A1 |
20060119882 | Harris et al. | Jun 2006 | A1 |
20060242239 | Morishima et al. | Oct 2006 | A1 |
20060252438 | Ansamaa et al. | Nov 2006 | A1 |
20060265417 | Amato et al. | Nov 2006 | A1 |
20060270419 | Crowiey et al. | Nov 2006 | A1 |
20060287878 | Wadhwa et al. | Dec 2006 | A1 |
20070004426 | Pfleging et al. | Jan 2007 | A1 |
20070038715 | Collins et al. | Feb 2007 | A1 |
20070040931 | Nishizawa | Feb 2007 | A1 |
20070064899 | Boss | Mar 2007 | A1 |
20070073517 | Panje | Mar 2007 | A1 |
20070073823 | Cohen et al. | Mar 2007 | A1 |
20070075898 | Markhovsky et al. | Apr 2007 | A1 |
20070082707 | Flynt et al. | Apr 2007 | A1 |
20070136228 | Petersen | Jun 2007 | A1 |
20070192128 | Celestini | Aug 2007 | A1 |
20070198340 | Lucovsky et al. | Aug 2007 | A1 |
20070198495 | Buron et al. | Aug 2007 | A1 |
20070208751 | Cowan et al. | Sep 2007 | A1 |
20070210936 | Nicholson | Sep 2007 | A1 |
20070214180 | Crawford | Sep 2007 | A1 |
20070214216 | Carrer et al. | Sep 2007 | A1 |
20070233556 | Koningstein | Oct 2007 | A1 |
20070233801 | Eren et al. | Oct 2007 | A1 |
20070233859 | Zhao et al. | Oct 2007 | A1 |
20070243887 | Bandhole et al. | Oct 2007 | A1 |
20070244750 | Grannan et al. | Oct 2007 | A1 |
20070255456 | Funayama | Nov 2007 | A1 |
20070281690 | Altman et al. | Dec 2007 | A1 |
20080022329 | Glad | Jan 2008 | A1 |
20080025701 | Ikeda | Jan 2008 | A1 |
20080032703 | Krumm et al. | Feb 2008 | A1 |
20080033930 | Warren | Feb 2008 | A1 |
20080043041 | Hedenstroem et al. | Feb 2008 | A2 |
20080049704 | Witteman et al. | Feb 2008 | A1 |
20080055269 | Lemay et al. | Mar 2008 | A1 |
20080062141 | Chandhri | Mar 2008 | A1 |
20080076505 | Ngyen et al. | Mar 2008 | A1 |
20080088623 | Bukowski et al. | Apr 2008 | A1 |
20080092233 | Tian et al. | Apr 2008 | A1 |
20080094387 | Chen | Apr 2008 | A1 |
20080104503 | Beall et al. | May 2008 | A1 |
20080109844 | Baldeschweiler et al. | May 2008 | A1 |
20080120409 | Sun et al. | May 2008 | A1 |
20080147730 | Lee et al. | Jun 2008 | A1 |
20080148150 | Mall | Jun 2008 | A1 |
20080158230 | Sharma et al. | Jul 2008 | A1 |
20080168033 | Ott et al. | Jul 2008 | A1 |
20080168489 | Schraga | Jul 2008 | A1 |
20080189177 | Anderton et al. | Aug 2008 | A1 |
20080207176 | Brackbill et al. | Aug 2008 | A1 |
20080208692 | Garaventi | Aug 2008 | A1 |
20080021421 | Rasanen et al. | Sep 2008 | A1 |
20080222545 | Lemay | Sep 2008 | A1 |
20080255976 | Altberg et al. | Oct 2008 | A1 |
20080256446 | Yamamoto | Oct 2008 | A1 |
20080256577 | Funaki et al. | Oct 2008 | A1 |
20080266421 | Takahata et al. | Oct 2008 | A1 |
20080270938 | Carlson | Oct 2008 | A1 |
20080273796 | Kansal et al. | Nov 2008 | A1 |
20080288338 | Wiseman et al. | Nov 2008 | A1 |
20080306826 | Kramer et al. | Dec 2008 | A1 |
20080313329 | Wang et al. | Dec 2008 | A1 |
20080313346 | Kujawa et al. | Dec 2008 | A1 |
20080318616 | Chipalkatti et al. | Dec 2008 | A1 |
20090006191 | Arankalle et al. | Jan 2009 | A1 |
20090006565 | Velusamy et al. | Jan 2009 | A1 |
20090015703 | Kim et al. | Jan 2009 | A1 |
20090024956 | Kobayashi | Jan 2009 | A1 |
20090030774 | Rothschild et al. | Jan 2009 | A1 |
20090030999 | Gatzke et al. | Jan 2009 | A1 |
20090040324 | Nonaka | Feb 2009 | A1 |
20090042588 | Lottin et al. | Feb 2009 | A1 |
20090058822 | Chaudhri | Mar 2009 | A1 |
20090079846 | Chou | Mar 2009 | A1 |
20090008971 | Wood et al. | Apr 2009 | A1 |
20090089678 | Sacco et al. | Apr 2009 | A1 |
20090093261 | Ziskind | Apr 2009 | A1 |
20090132341 | Klinger | May 2009 | A1 |
20090132453 | Hangartner et al. | May 2009 | A1 |
20090132665 | Thomsen et al. | May 2009 | A1 |
20090148045 | Lee et al. | Jun 2009 | A1 |
20090153492 | Popp | Jun 2009 | A1 |
20090157450 | Athsani et al. | Jun 2009 | A1 |
20090157752 | Gonzalez | Jun 2009 | A1 |
20090160970 | Fredlund et al. | Jun 2009 | A1 |
20090163182 | Gatti et al. | Jun 2009 | A1 |
20090177299 | Van De Sluis | Jul 2009 | A1 |
20090192900 | Collision | Jul 2009 | A1 |
20090199242 | Johnson et al. | Aug 2009 | A1 |
20090215469 | Fisher | Aug 2009 | A1 |
20090232354 | Camp, Jr. et al. | Sep 2009 | A1 |
20090234815 | Boerries et al. | Sep 2009 | A1 |
20090239552 | Churchill et al. | Sep 2009 | A1 |
20090249222 | Schmidt et al. | Oct 2009 | A1 |
20090249244 | Robinson et al. | Oct 2009 | A1 |
20090265647 | Martin et al. | Oct 2009 | A1 |
20090288022 | Almstrand et al. | Nov 2009 | A1 |
20090291672 | Treves et al. | Nov 2009 | A1 |
20090292608 | Poiachek | Nov 2009 | A1 |
20090293012 | Alter et al. | Nov 2009 | A1 |
20090319607 | Belz et al. | Dec 2009 | A1 |
20090327073 | Li | Dec 2009 | A1 |
20100062794 | Han | Mar 2010 | A1 |
20100082427 | Burgener et al. | Apr 2010 | A1 |
20100082693 | Hugg et al. | Apr 2010 | A1 |
20100100568 | Papin et al. | Apr 2010 | A1 |
20100113065 | Narayan et al. | May 2010 | A1 |
20100130233 | Lansing | May 2010 | A1 |
20100131880 | Lee et al. | May 2010 | A1 |
20100131895 | Wohlert | May 2010 | A1 |
20100153144 | Miller et al. | Jun 2010 | A1 |
20100159944 | Pascal et al. | Jun 2010 | A1 |
20100161658 | Hamynen et al. | Jun 2010 | A1 |
20100161831 | Haas et al. | Jun 2010 | A1 |
20100162138 | Pascal et al. | Jun 2010 | A1 |
20100162149 | Sheleheda et al. | Jun 2010 | A1 |
20100183280 | Beauregard et al. | Jul 2010 | A1 |
20100185552 | Deluca et al. | Jul 2010 | A1 |
20100185665 | Horn et al. | Jul 2010 | A1 |
20100191631 | Weidmann | Jul 2010 | A1 |
20100197318 | Petersen et al. | Aug 2010 | A1 |
20100197319 | Petersen et al. | Aug 2010 | A1 |
20100198683 | Aarabi | Aug 2010 | A1 |
20100198694 | Muthukrishnan | Aug 2010 | A1 |
20100198826 | Petersen et al. | Aug 2010 | A1 |
20100198828 | Petersen et al. | Aug 2010 | A1 |
20100198862 | Jennings et al. | Aug 2010 | A1 |
20100198870 | Petersen et al. | Aug 2010 | A1 |
20100198917 | Petersen et al. | Aug 2010 | A1 |
20100201482 | Robertson et al. | Aug 2010 | A1 |
20100201536 | Robertson et al. | Aug 2010 | A1 |
20100214436 | Kim et al. | Aug 2010 | A1 |
20100223128 | Dukellis et al. | Sep 2010 | A1 |
20100223343 | Bosan et al. | Sep 2010 | A1 |
20100250109 | Johnston et al. | Sep 2010 | A1 |
20100257196 | Waters et al. | Oct 2010 | A1 |
20100259386 | Holley et al. | Oct 2010 | A1 |
20100273509 | Sweeney et al. | Oct 2010 | A1 |
20100281045 | Dean | Nov 2010 | A1 |
20100287485 | Bertolami et al. | Nov 2010 | A1 |
20100306669 | Della Pasqua | Dec 2010 | A1 |
20100315418 | Woo | Dec 2010 | A1 |
20100316280 | Lancaster et al. | Dec 2010 | A1 |
20110004071 | Faiola et al. | Jan 2011 | A1 |
20110010205 | Richards | Jan 2011 | A1 |
20110029512 | Folgner et al. | Feb 2011 | A1 |
20110040783 | Uemichi et al. | Feb 2011 | A1 |
20110040804 | Peirce et al. | Feb 2011 | A1 |
20110050909 | Ellenby et al. | Mar 2011 | A1 |
20110050915 | Wang et al. | Mar 2011 | A1 |
20110064388 | Brown et al. | Mar 2011 | A1 |
20110066743 | Hurley et al. | Mar 2011 | A1 |
20110083101 | Sharon et al. | Apr 2011 | A1 |
20110090253 | Good | Apr 2011 | A1 |
20110096093 | Oi et al. | Apr 2011 | A1 |
20110099507 | Nesladek | Apr 2011 | A1 |
20110102630 | Rukes | May 2011 | A1 |
20110119133 | Igelman et al. | May 2011 | A1 |
20110137881 | Cheng et al. | Jun 2011 | A1 |
20110145564 | Moshir et al. | Jun 2011 | A1 |
20110159890 | Fortescue et al. | Jun 2011 | A1 |
20110164163 | Bilbrey et al. | Jul 2011 | A1 |
20110197194 | D'Angelo et al. | Aug 2011 | A1 |
20110202598 | Evans et al. | Aug 2011 | A1 |
20110202968 | Nurmi | Aug 2011 | A1 |
20110211534 | Schmidt et al. | Sep 2011 | A1 |
20110213845 | Logan et al. | Sep 2011 | A1 |
20110215966 | Kim et al. | Sep 2011 | A1 |
20110225048 | Nair | Sep 2011 | A1 |
20110238763 | Shin et al. | Sep 2011 | A1 |
20110255736 | Thompson et al. | Oct 2011 | A1 |
20110270584 | Plocher et al. | Nov 2011 | A1 |
20110273575 | Lee | Nov 2011 | A1 |
20110279445 | Murphy et al. | Nov 2011 | A1 |
20110279446 | Castro et al. | Nov 2011 | A1 |
20110279453 | Murphy et al. | Nov 2011 | A1 |
20110282799 | Huston | Nov 2011 | A1 |
20110283188 | Farrenkopf | Nov 2011 | A1 |
20110286586 | Saylor et al. | Nov 2011 | A1 |
20110314419 | Dunn et al. | Dec 2011 | A1 |
20110320373 | Lee et al. | Dec 2011 | A1 |
20120028659 | Whitney et al. | Feb 2012 | A1 |
20120033718 | Kauffman et al. | Feb 2012 | A1 |
20120036015 | Sheikh | Feb 2012 | A1 |
20120036443 | Ohmori et al. | Feb 2012 | A1 |
20120041722 | Quan et al. | Feb 2012 | A1 |
20120054797 | Skog et al. | Mar 2012 | A1 |
20120059722 | Rao | Mar 2012 | A1 |
20120062805 | Candelore | Mar 2012 | A1 |
20120069233 | Nonaka et al. | Mar 2012 | A1 |
20120084731 | Filman et al. | Apr 2012 | A1 |
20120084835 | Thomas et al. | Apr 2012 | A1 |
20120086727 | Korah et al. | Apr 2012 | A1 |
20120092329 | Koo et al. | Apr 2012 | A1 |
20120099800 | Llano et al. | Apr 2012 | A1 |
20120108293 | Law et al. | May 2012 | A1 |
20120110096 | Smarr et al. | May 2012 | A1 |
20120113143 | Adhikari et al. | May 2012 | A1 |
20120113272 | Hata | May 2012 | A1 |
20120122570 | Baronoff | May 2012 | A1 |
20120123830 | Svendsen et al. | May 2012 | A1 |
20120123871 | Svendsen et al. | May 2012 | A1 |
20120123875 | Svendsen et al. | May 2012 | A1 |
20120124126 | Alcazar et al. | May 2012 | A1 |
20120124176 | Curtis et al. | May 2012 | A1 |
20120124458 | Cruzada | May 2012 | A1 |
20120131507 | Sparandara et al. | May 2012 | A1 |
20120131512 | Takeuchi et al. | May 2012 | A1 |
20120143760 | Abulafia et al. | Jun 2012 | A1 |
20120146991 | Bala et al. | Jun 2012 | A1 |
20120150978 | Monaco | Jun 2012 | A1 |
20120165100 | Lalancette et al. | Jun 2012 | A1 |
20120166971 | Sachson et al. | Jun 2012 | A1 |
20120169855 | Oh | Jul 2012 | A1 |
20120172062 | Altman et al. | Jul 2012 | A1 |
20120173991 | Roberts et al. | Jul 2012 | A1 |
20120176401 | Hayward et al. | Jul 2012 | A1 |
20120181330 | Kim | Jul 2012 | A1 |
20120184248 | Speede | Jul 2012 | A1 |
20120197724 | Kendall | Aug 2012 | A1 |
20120200743 | Blanchflower et al. | Aug 2012 | A1 |
20120209921 | Adafin et al. | Aug 2012 | A1 |
20120209924 | Evans et al. | Aug 2012 | A1 |
20120210244 | De Francisco Lopez et al. | Aug 2012 | A1 |
20120212509 | Benko et al. | Aug 2012 | A1 |
20120212632 | Mate et al. | Aug 2012 | A1 |
20120220264 | Kawabata | Aug 2012 | A1 |
20120226748 | Bosworth et al. | Sep 2012 | A1 |
20120233000 | Fisher et al. | Sep 2012 | A1 |
20120236162 | Imamura | Sep 2012 | A1 |
20120239761 | Linner et al. | Sep 2012 | A1 |
20120240077 | Vaittinen et al. | Sep 2012 | A1 |
20120250951 | Chen | Oct 2012 | A1 |
20120252418 | Kandekar et al. | Oct 2012 | A1 |
20120254325 | Majeti et al. | Oct 2012 | A1 |
20120278387 | Garcia et al. | Nov 2012 | A1 |
20120278692 | Shi | Nov 2012 | A1 |
20120290637 | Perantatos et al. | Nov 2012 | A1 |
20120297451 | Ozzie | Nov 2012 | A1 |
20120299954 | Wada et al. | Nov 2012 | A1 |
20120304052 | Tanaka et al. | Nov 2012 | A1 |
20120304080 | Wormald et al. | Nov 2012 | A1 |
20120307096 | Ford et al. | Dec 2012 | A1 |
20120307112 | Kunishige et al. | Dec 2012 | A1 |
20120314040 | Kopf et al. | Dec 2012 | A1 |
20120319904 | Lee et al. | Dec 2012 | A1 |
20120323933 | He et al. | Dec 2012 | A1 |
20120324018 | Metcalf et al. | Dec 2012 | A1 |
20120330646 | Andrade et al. | Dec 2012 | A1 |
20130002649 | Wu et al. | Jan 2013 | A1 |
20130004068 | Koo et al. | Jan 2013 | A1 |
20130006759 | Srivastava et al. | Jan 2013 | A1 |
20130024757 | Doll et al. | Jan 2013 | A1 |
20130036364 | Johnson | Feb 2013 | A1 |
20130045753 | Obermeyer et al. | Feb 2013 | A1 |
20130050260 | Reitan | Feb 2013 | A1 |
20130055083 | Fino | Feb 2013 | A1 |
20130057587 | Leonard et al. | Mar 2013 | A1 |
20130059607 | Herz et al. | Mar 2013 | A1 |
20130060690 | Oskolkov et al. | Mar 2013 | A1 |
20130060911 | Nagaraj et al. | Mar 2013 | A1 |
20130063369 | Malhotra et al. | Mar 2013 | A1 |
20130067027 | Song et al. | Mar 2013 | A1 |
20130071093 | Hanks et al. | Mar 2013 | A1 |
20130080254 | Thramann | Mar 2013 | A1 |
20130085790 | Palmer et al. | Apr 2013 | A1 |
20130086072 | Peng et al. | Apr 2013 | A1 |
20130090171 | Holton et al. | Apr 2013 | A1 |
20130095857 | Garcia et al. | Apr 2013 | A1 |
20130103383 | Du et al. | Apr 2013 | A1 |
20130104053 | Thornton et al. | Apr 2013 | A1 |
20130110885 | Brundrett, III | May 2013 | A1 |
20130111514 | Slavin et al. | May 2013 | A1 |
20130128059 | Kristensson | May 2013 | A1 |
20130129252 | Lauper | May 2013 | A1 |
20130132477 | Bosworth et al. | May 2013 | A1 |
20130141419 | Mount et al. | Jun 2013 | A1 |
20130145286 | Feng et al. | Jun 2013 | A1 |
20130159110 | Rajaram et al. | Jun 2013 | A1 |
20130159919 | Leydon | Jun 2013 | A1 |
20130169680 | Chien et al. | Jul 2013 | A1 |
20130169822 | Zhu et al. | Jul 2013 | A1 |
20130173729 | Starenky et al. | Jul 2013 | A1 |
20130181971 | Mueller | Jul 2013 | A1 |
20130182133 | Tanabe | Jul 2013 | A1 |
20130185131 | Sinha et al. | Jul 2013 | A1 |
20130187952 | Berkovich et al. | Jul 2013 | A1 |
20130191198 | Carlson et al. | Jul 2013 | A1 |
20130194164 | Sugden et al. | Aug 2013 | A1 |
20130194301 | Robbins et al. | Aug 2013 | A1 |
20130198176 | Kim | Aug 2013 | A1 |
20130215101 | Duan | Aug 2013 | A1 |
20130218965 | Abrol et al. | Aug 2013 | A1 |
20130218968 | Mcevilly et al. | Aug 2013 | A1 |
20130222323 | Mckenzie | Aug 2013 | A1 |
20130227476 | Frey | Aug 2013 | A1 |
20130232194 | Knapp et al. | Sep 2013 | A1 |
20130263031 | Oshiro et al. | Oct 2013 | A1 |
20130265450 | Barnes, Jr. | Oct 2013 | A1 |
20130267253 | Case et al. | Oct 2013 | A1 |
20130275505 | Gauglitz et al. | Oct 2013 | A1 |
20130290443 | Collins et al. | Oct 2013 | A1 |
20130304646 | De Geer | Nov 2013 | A1 |
20130308822 | Marimon et al. | Nov 2013 | A1 |
20130311255 | Cummins et al. | Nov 2013 | A1 |
20130325964 | Berberat | Dec 2013 | A1 |
20130332066 | Jeung et al. | Dec 2013 | A1 |
20130344896 | Kirmse et al. | Dec 2013 | A1 |
20130346869 | Asver et al. | Dec 2013 | A1 |
20130346877 | Borovoy et al. | Dec 2013 | A1 |
20140006129 | Heath | Jan 2014 | A1 |
20140011538 | Mulcahy et al. | Jan 2014 | A1 |
20140019264 | Wachman et al. | Jan 2014 | A1 |
20140029798 | Flynn et al. | Jan 2014 | A1 |
20140032682 | Prado et al. | Jan 2014 | A1 |
20140043204 | Basnayake et al. | Feb 2014 | A1 |
20140045530 | Gordon et al. | Feb 2014 | A1 |
20140047016 | Rao | Feb 2014 | A1 |
20140047045 | Baldwin et al. | Feb 2014 | A1 |
20140047335 | Lewis et al. | Feb 2014 | A1 |
20140049652 | Moon et al. | Feb 2014 | A1 |
20140052485 | Shidfar | Feb 2014 | A1 |
20140052633 | Gandhi | Feb 2014 | A1 |
20140057660 | Wager | Feb 2014 | A1 |
20140064624 | Kim et al. | Mar 2014 | A1 |
20140081634 | Forutanpour | Mar 2014 | A1 |
20140082651 | Sharifi | Mar 2014 | A1 |
20140086727 | Xu | Mar 2014 | A1 |
20140092130 | Anderson et al. | Apr 2014 | A1 |
20140096029 | Schultz | Apr 2014 | A1 |
20140114565 | Aziz et al. | Apr 2014 | A1 |
20140122658 | Haeger et al. | May 2014 | A1 |
20140122787 | Shalvi et al. | May 2014 | A1 |
20140125658 | Bell et al. | May 2014 | A1 |
20140125668 | Steed et al. | May 2014 | A1 |
20140129207 | Bailey et al. | May 2014 | A1 |
20140129953 | Spiegel | May 2014 | A1 |
20140143143 | Fasoli et al. | May 2014 | A1 |
20140149519 | Redfern et al. | May 2014 | A1 |
20140155102 | Cooper et al. | Jun 2014 | A1 |
20140173424 | Hogeg et al. | Jun 2014 | A1 |
20140173457 | Wang et al. | Jun 2014 | A1 |
20140189592 | Benchenaa et al. | Jul 2014 | A1 |
20140201527 | Krivorot | Jul 2014 | A1 |
20140207679 | Cho | Jul 2014 | A1 |
20140214471 | Schreiner, III | Jul 2014 | A1 |
20140222564 | Kranendonk et al. | Aug 2014 | A1 |
20140232743 | Na et al. | Aug 2014 | A1 |
20140258405 | Perkin | Sep 2014 | A1 |
20140265359 | Cheng et al. | Sep 2014 | A1 |
20140266703 | Dalley, Jr. et al. | Sep 2014 | A1 |
20140277735 | Breazeal | Sep 2014 | A1 |
20140279061 | Elimeliah et al. | Sep 2014 | A1 |
20140279436 | Dorsey et al. | Sep 2014 | A1 |
20140279540 | Jackson | Sep 2014 | A1 |
20140280537 | Pridmore et al. | Sep 2014 | A1 |
20140282096 | Rubinstein et al. | Sep 2014 | A1 |
20140287779 | O'keefe et al. | Sep 2014 | A1 |
20140289833 | Briceno | Sep 2014 | A1 |
20140301645 | Mattila | Oct 2014 | A1 |
20140306986 | Gottesman et al. | Oct 2014 | A1 |
20140317302 | Naik | Oct 2014 | A1 |
20140324627 | Haver et al. | Oct 2014 | A1 |
20140324629 | Jacobs | Oct 2014 | A1 |
20140325383 | Brown et al. | Oct 2014 | A1 |
20140359024 | Spiegel | Dec 2014 | A1 |
20140359032 | Spiegel et al. | Dec 2014 | A1 |
20150002506 | Saarimäki et al. | Jan 2015 | A1 |
20150020086 | Chen et al. | Jan 2015 | A1 |
20150040074 | Hofmann et al. | Feb 2015 | A1 |
20150046278 | Pei et al. | Feb 2015 | A1 |
20150071619 | Brough | Mar 2015 | A1 |
20150087263 | Branscomb et al. | Mar 2015 | A1 |
20150088622 | Ganschow et al. | Mar 2015 | A1 |
20150092038 | Jantunen | Apr 2015 | A1 |
20150095020 | Leydon | Apr 2015 | A1 |
20150096042 | Mizrachi | Apr 2015 | A1 |
20150116529 | Wu et al. | Apr 2015 | A1 |
20150169827 | Laborde | Jun 2015 | A1 |
20150172534 | Miyakawa et al. | Jun 2015 | A1 |
20150178257 | Jones et al. | Jun 2015 | A1 |
20150178260 | Brunson | Jun 2015 | A1 |
20150193982 | Mihelich et al. | Jul 2015 | A1 |
20150199082 | Scholler et al. | Jul 2015 | A1 |
20150222814 | Li et al. | Aug 2015 | A1 |
20150227602 | Ramu et al. | Aug 2015 | A1 |
20150228122 | Sadasue | Aug 2015 | A1 |
20150261917 | Smith | Sep 2015 | A1 |
20150294503 | Yang et al. | Oct 2015 | A1 |
20150312184 | Langholz et al. | Oct 2015 | A1 |
20150347854 | Bare et al. | Dec 2015 | A1 |
20150350136 | Flynn, III et al. | Dec 2015 | A1 |
20150365795 | Allen et al. | Dec 2015 | A1 |
20150378502 | Hu et al. | Dec 2015 | A1 |
20160006927 | Sehn | Jan 2016 | A1 |
20160014063 | Hogeg et al. | Jan 2016 | A1 |
20160019239 | Bastaldo-Tsampalis et al. | Jan 2016 | A1 |
20160019270 | Jones et al. | Jan 2016 | A1 |
20160021038 | Woo et al. | Jan 2016 | A1 |
20160021039 | Woo et al. | Jan 2016 | A1 |
20160085773 | Chang et al. | Mar 2016 | A1 |
20160085863 | Allen et al. | Mar 2016 | A1 |
20160086384 | Stroila | Mar 2016 | A1 |
20160086670 | Gross et al. | Mar 2016 | A1 |
20160091964 | Iyer et al. | Mar 2016 | A1 |
20160099901 | Allen et al. | Apr 2016 | A1 |
20160104452 | Guan et al. | Apr 2016 | A1 |
20160180887 | Sehn | Jun 2016 | A1 |
20160182422 | Sehn et al. | Jun 2016 | A1 |
20160182875 | Sehn | Jun 2016 | A1 |
20160203586 | Chang et al. | Jul 2016 | A1 |
20160239248 | Sehn | Aug 2016 | A1 |
20160253710 | Publicover et al. | Sep 2016 | A1 |
20160266386 | Scott et al. | Sep 2016 | A1 |
20160277419 | Allen et al. | Sep 2016 | A1 |
20160321708 | Sehn | Nov 2016 | A1 |
20160352791 | Adams et al. | Dec 2016 | A1 |
20160359957 | Laliberte | Dec 2016 | A1 |
20160359987 | Laliberte | Dec 2016 | A1 |
20160371884 | Benko et al. | Dec 2016 | A1 |
20170006094 | Abou Mahmoud et al. | Jan 2017 | A1 |
20170061308 | Chen et al. | Mar 2017 | A1 |
20170103124 | Hassan | Apr 2017 | A1 |
20170124713 | Jurgenson et al. | May 2017 | A1 |
20170161382 | Ouimet et al. | Jun 2017 | A1 |
20170161558 | Ludwigsen et al. | Jun 2017 | A1 |
20170200296 | Jones et al. | Jul 2017 | A1 |
20170228878 | Goldman et al. | Aug 2017 | A1 |
20170237789 | Harner et al. | Aug 2017 | A1 |
20170243371 | Jurgenson et al. | Aug 2017 | A1 |
20170263029 | Yan et al. | Sep 2017 | A1 |
20170287006 | Azmoodeh et al. | Oct 2017 | A1 |
20170289623 | Bailey et al. | Oct 2017 | A1 |
20170295250 | Samaranayake et al. | Oct 2017 | A1 |
20170308272 | Levien et al. | Oct 2017 | A1 |
20170372526 | Groten et al. | Dec 2017 | A1 |
20170374003 | Allen et al. | Dec 2017 | A1 |
20170374508 | Davis et al. | Dec 2017 | A1 |
20180005450 | Daniels et al. | Jan 2018 | A1 |
20180061127 | Gullicksen | Mar 2018 | A1 |
20180089904 | Jurgenson et al. | Mar 2018 | A1 |
20180096502 | Kansara | Apr 2018 | A1 |
20180144524 | Lotto et al. | May 2018 | A1 |
20180189552 | Barnett et al. | Jul 2018 | A1 |
20180204372 | Sudheendra et al. | Jul 2018 | A1 |
20180300916 | Barnett et al. | Oct 2018 | A1 |
20180300917 | Barnett et al. | Oct 2018 | A1 |
20190068529 | Mullins | Feb 2019 | A1 |
20190073832 | Kim | Mar 2019 | A1 |
20190138597 | Dowell et al. | May 2019 | A1 |
20190156534 | Chen et al. | May 2019 | A1 |
20190295326 | Jurgenson et al. | Sep 2019 | A1 |
20190347323 | Riesa et al. | Nov 2019 | A1 |
20200058151 | Stukalov | Feb 2020 | A1 |
20200074705 | Berger et al. | Mar 2020 | A1 |
20200219312 | Jurgenson et al. | Jul 2020 | A1 |
20200250889 | Li | Aug 2020 | A1 |
20200327738 | Jurgenson et al. | Oct 2020 | A1 |
20210056760 | Cowburn et al. | Feb 2021 | A1 |
20210166455 | Berger et al. | Jun 2021 | A1 |
20210174578 | Jurgenson et al. | Jun 2021 | A1 |
20210304369 | Mccormack et al. | Sep 2021 | A1 |
20210407533 | Cowburn et al. | Dec 2021 | A1 |
20220076017 | Cowburn et al. | Mar 2022 | A1 |
20220301122 | Mccormack et al. | Sep 2022 | A1 |
20220406008 | Jurgenson et al. | Dec 2022 | A1 |
20230222743 | Cowburn et al. | Jul 2023 | A1 |
Number | Date | Country |
---|---|---|
2887596 | Jul 2015 | CA |
101893935 | Nov 2010 | CN |
103471580 | Dec 2013 | CN |
103513951 | Jan 2014 | CN |
104428817 | Mar 2015 | CN |
104899920 | Sep 2015 | CN |
104995583 | Oct 2015 | CN |
112639892 | Apr 2021 | CN |
113396443 | Sep 2021 | CN |
115335820 | Nov 2022 | CN |
2051480 | Apr 2009 | EP |
2151797 | Feb 2010 | EP |
2439676 | Apr 2012 | EP |
3147816 | Mar 2017 | EP |
3369076 | Sep 2018 | EP |
2399928 | Sep 2004 | GB |
19990073076 | Oct 1999 | KR |
20010078417 | Aug 2001 | KR |
20110071210 | Jun 2011 | KR |
20120061696 | Jun 2012 | KR |
20130091991 | Aug 2013 | KR |
20130137063 | Dec 2013 | KR |
20180087918 | Aug 2018 | KR |
102052018 | Dec 2019 | KR |
102205689 | Jan 2021 | KR |
102274272 | Jul 2021 | KR |
20220154816 | Nov 2022 | KR |
2021252201 | Dec 2021 | NO |
WO-1996024213 | Aug 1996 | WO |
WO-1999063453 | Dec 1999 | WO |
WO-2000058882 | Oct 2000 | WO |
WO-2001029642 | Apr 2001 | WO |
WO-2001050703 | Jul 2001 | WO |
WO-2006118755 | Nov 2006 | WO |
WO-2007092668 | Aug 2007 | WO |
WO-2009043020 | Apr 2009 | WO |
WO-2011040821 | Apr 2011 | WO |
WO-2011119407 | Sep 2011 | WO |
WO-2012000107 | Jan 2012 | WO |
WO-2013003242 | Jan 2013 | WO |
WO-2013008238 | Jan 2013 | WO |
WO-2013008251 | Jan 2013 | WO |
WO-2013045753 | Apr 2013 | WO |
WO-2014006129 | Jan 2014 | WO |
WO-2014011346 | Jan 2014 | WO |
WO-2014068573 | May 2014 | WO |
WO-2014115136 | Jul 2014 | WO |
WO-2014194262 | Dec 2014 | WO |
WO-2015192026 | Dec 2015 | WO |
WO-2016044424 | Mar 2016 | WO |
WO-2016054562 | Apr 2016 | WO |
WO-2016065131 | Apr 2016 | WO |
WO-2016100318 | Jun 2016 | WO |
WO-2016100318 | Jun 2016 | WO |
WO-2016100342 | Jun 2016 | WO |
WO-2016112299 | Jul 2016 | WO |
WO-2016149594 | Sep 2016 | WO |
WO-2016179166 | Nov 2016 | WO |
WO-2016179235 | Nov 2016 | WO |
WO-2017075476 | May 2017 | WO |
WO-2017120660 | Jul 2017 | WO |
WO-2017176739 | Oct 2017 | WO |
WO-2017176992 | Oct 2017 | WO |
WO-2018005644 | Jan 2018 | WO |
WO-2020047259 | Mar 2020 | WO |
WO-2020160261 | Aug 2020 | WO |
2021195670 | Sep 2021 | WO |
2022147031 | Jul 2022 | WO |
Entry |
---|
“U.S. Appl. No. 15/706,074, Examiner Interview Summary dated Feb. 5, 2020”, 3 pgs. |
“U.S. Appl. No. 15/706,074, Examiner Interview Summary dated Jul. 3, 2019”, 3 pgs. |
“U.S. Appl. No. 15/706,074, Examiner Interview Summary dated Nov. 1, 2019”, 3 pgs. |
“U.S. Appl. No. 15/706,074, Final Office Action dated Dec. 19, 2019”, 32 pgs. |
“U.S. Appl. No. 15/706,074, Non Final Office Action dated Sep. 18, 2019”, 29 pgs. |
“U.S. Appl. No. 15/706,074, Notice of Allowance dated Mar. 30, 2020”, 5 pgs. |
“U.S. Appl. No. 15/706,074, Response filed Mar. 19, 2020 to Final Office Action dated Dec. 19, 2019”, 12 pgs. |
“U.S. Appl. No. 15/706,074, Response filed Jul. 8, 2019 to Final Office Action dated May 10, 2019”, 17 pgs. |
“U.S. Appl. No. 15/706,074, Response filed Nov. 11, 2019 to Non Final Office Action dated Sep. 18, 2019”, 13 pgs. |
“U.S. Appl. No. 16/119,397, Final Office Action dated May 21, 2020”, 17 pgs. |
“U.S. Appl. No. 16/119,397, Final Office Action dated Aug. 21, 2020”, 18 pgs. |
“U.S. Appl. No. 16/119,397, Non Final Office Action dated Jun. 19, 2020”, 17 pgs. |
“U.S. Appl. No. 16/119,397, Non Final Office Action dated Oct. 1, 2020”, 18 pgs. |
“U.S. Appl. No. 16/119,397, Non Final Office Action dated Nov. 15, 2019”, 14 pgs. |
“U.S. Appl. No. 16/119,397, Notice of Allowance dated Dec. 28, 2020”, 9 pgs. |
“U.S. Appl. No. 16/119,397, Response filed Feb. 18, 2020 to Non Final Office Action dated Nov. 15, 2019”, 12 pgs. |
“U.S. Appl. No. 16/119,397, Response filed May 29, 2020 to Final Office Action dated May 21, 2020”, 12 pgs. |
“U.S. Appl. No. 16/119,397, Response filed Jul. 14, 2020 to Non Final Office Action dated Jun. 19, 2020”, 12 pgs. |
“U.S. Appl. No. 16/119,397, Response filed Sep. 2, 2020 to Final Office Action dated Aug. 21, 2020”, 12 pgs. |
“U.S. Appl. No. 16/119,397, Response filed Nov. 16, 2020 to Non Final Office Action dated Oct. 1, 2020”, 13 pgs. |
“U.S. Appl. No. 16/265,382, Advisory Action dated Jan. 12, 2022”, 4 pgs. |
“U.S. Appl. No. 16/265,382, Final Office Action dated Oct. 13, 2020”, 21 pgs. |
“U.S. Appl. No. 16/265,382, Final Office Action dated Oct. 29, 2021”, 22 pgs. |
“U.S. Appl. No. 16/265,382, Non Final Office Action dated May 24, 2021”, 23 pgs. |
“U.S. Appl. No. 16/265,382, Response filed Feb. 12, 2021 to Final Office Action dated Oct. 13, 2020”, 11 pgs. |
“U.S. Appl. No. 16/265,382, Response filed Mar. 29, 2022 to Advisory Action dated Jan. 12, 2022”, 11 pgs. |
“U.S. Appl. No. 16/265,382, Response filed Aug. 3, 2020 to Non Final Office Action dated Mar. 3, 2020”, 10 pgs. |
“U.S. Appl. No. 16/265,382, Response filed Sep. 24, 2021 to Non Final Office Action dated May 24, 2021”, 11 pgs. |
“U.S. Appl. No. 16/265,382, Response filed Dec. 29, 2021 to Final Office Action dated Oct. 29, 2021”, 11 pgs. |
“U.S. Appl. No. 16/277,626, Final Office Action dated Apr. 15, 2022”, 23 pgs. |
“U.S. Appl. No. 16/277,626, Final Office Action dated Aug. 19, 2022”, 23 pgs. |
“U.S. Appl. No. 16/277,626, Final Office Action dated Nov. 14, 2022”, 30 pgs. |
“U.S. Appl. No. 16/277,626, Non Final Office Action dated Jul. 12, 2022”, 22 pgs. |
“U.S. Appl. No. 16/277,626, Non Final Office Action dated Oct. 7, 2022”, 25 pgs. |
“U.S. Appl. No. 16/277,626, Response filed Jan. 10, 2023 to Final Office Action dated Nov. 14, 2022”, 11 pgs. |
“U.S. Appl. No. 16/277,626, Response filed Mar. 29, 2022 to Non Final Office Action dated Nov. 29, 2021”, 9 pgs. |
“U.S. Appl. No. 16/277,626, Response filed May 13, 2022 to Final Office Action dated Apr. 15, 2022”, 10 pgs. |
“U.S. Appl. No. 16/277,626, Response filed Jul. 27, 2022 to Non Final Office Action dated Jul. 12, 2022”, 10 pgs. |
“U.S. Appl. No. 16/277,626, Response filed Sep. 15, 2022 to Final Office Action dated Aug. 19, 2022”, 10 pgs. |
“U.S. Appl. No. 16/277,626, Response filed Oct. 26, 2022 to Non Final Office Action dated Oct. 7, 2022”, 11 pgs. |
“U.S. Appl. No. 16/921,487, Final Office Action dated Oct. 15, 2021”, 22 pgs. |
“U.S. Appl. No. 16/921,487, Non Final Office Action dated Jun. 10, 2021”, 19 pgs. |
“U.S. Appl. No. 16/921,487, Preliminary Amendment filed Nov. 16, 2020”, 8 pgs. |
“U.S. Appl. No. 16/921,487, Response filed Sep. 10, 2021 to Non Final Office Action dated Jun. 10, 2021”, 12 pgs. |
“U.S. Appl. No. 17/248,833, 312 Amendment filed May 24, 2022”, 10 pgs. |
“U.S. Appl. No. 17/248,833, Notice of Allowance dated Feb. 24, 2022”, 7 pgs. |
“U.S. Appl. No. 17/248,833, PTO Response to Rule 312 Communication dated Jun. 2, 2022”, 2 pgs. |
“U.S. Appl. No. 17/248,833, Response filed Jan. 27, 2022 to Non Final Office Action dated Sep. 30, 2021”, 11 pgs. |
“U.S. Appl. No. 17/248,833, Supplemental Notice of Allowability dated May 18, 2022”, 2 pgs. |
“U.S. Appl. No. 17/248,835, Non Final Office Action dated Oct. 1, 2021”, 18 pgs. |
“U.S. Appl. No. 17/856,720, Preliminary Amendment filed Sep. 13, 2022”, 9 pgs. |
“Chinese Application Serial No. 201680035045.X, Decision of Rejection dated Feb. 15, 2022”, w/ English Translation, 23 pgs. |
“Chinese Application Serial No. 201680035045.X, Office Action dated Oct. 10, 2022”, w/English translation, 7 pgs. |
“European Application Serial No. 16795488.2, Communication Pursuant to Article 94(3) EPC dated Feb. 16, 2022”, 4 pgs. |
“European Application Serial No. 19854093.2, Extended European Search Report dated Sep. 27, 2021”, 7 pgs. |
“International Application Serial No. PCT/US2019/048817, International Preliminary Report on Patentability dated Mar. 11, 2021”, 7 pgs. |
“International Application Serial No. PCT/US2019/048817, International Search Report dated Dec. 13, 2019”, 3 pgs. |
“International Application Serial No. PCT/US2019/048817, Written Opinion dated Dec. 13, 2019”, 5 pgs. |
“International Application Serial No. PCT/US2020/015868, International Preliminary Report on Patentability dated Aug. 12, 2021”, 17 pgs. |
“International Application Serial No. PCT/US2020/015868, International Search Report dated Jul. 10, 2020”, 6 pgs. |
“International Application Serial No. PCT/US2020/015868, Invitation to Pay Additional Fees dated May 19, 2020”, 14 pgs. |
“International Application Serial No. PCT/US2020/015868, Written Opinion dated Jul. 10, 2020”, 15 pgs. |
“Skrite Full Length Commercial”, Youtube, [Online] Retrieved from the Internet: <URL: https://www.youtube.com/watch?v=nNx5VeSpk_Y>, (Jun. 27, 2017), 62 pgs.; 1:00 min. |
Park, Jungsik, et al., “Interactive Deformation of Real Objects”, IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Science and Technology Proceedings, Munich, DE, (Sep. 2014), 295-296. |
Raskar, Ramesh, et al., “Table-top spatially-augmented realty: bringing physical models to life with projected imagery”, Proceedings 2nd IEEE and ACM International Workshop on Augmented Reality (IWAR'99), San Francisco, USA, (Oct. 20-21, 1999), 64-71. |
Taejin, Ha, et al., “ARtalet: Tangible User Interface Based Immersive Augmented Reality Authoring Tool for Digilog Book”, IEEE Computer Society, International Symposium on Ubiquitous Virtual Reality, Gwangju, South Korea, (Jul. 7-10, 2010), 40-43. |
“A Whole New Story”, Snap, Inc., [Online] Retrieved from the Internet: <URL: https://www.snap.com/en-US/news/>, (2017), 13 pgs. |
“Adding photos to your listing”, eBay, [Online] Retrieved from the Internet: <URL: http://pages.ebay.com/help/sell/pictures.html>, (accessed May 24, 2017), 4 pgs. |
“U.S. Appl. No. 14/053,913, Response filed Nov. 13, 2017 to Non Final Office Action dated Jun. 12, 2017”, 11 pgs. |
“U.S. Appl. No. 14/953,913, Non Final Office Action dated Jun. 12, 2017”, 35 pgs. |
“U.S. Appl. No. 14/953,913, Notice of Allowance dated Jan. 30, 2018”, 23 pgs. |
“U.S. Appl. No. 14/954,090, Corrected Notice of Allowance dated Feb. 3, 2017”, 4 pgs. |
“U.S. Appl. No. 14/954,090, Corrected Notice of Allowance dated Apr. 18, 2017”, 4 pgs. |
“U.S. Appl. No. 14/954,090, Notice of Allowance dated Jan. 11, 2017”, 11 pgs. |
“U.S. Appl. No. 14/954,090, Preliminary Amendment filed Dec. 28, 2016”, 10 pgs. |
“U.S. Appl. No. 15/436,363, Examiner interview Summary dated Nov. 28, 2018”, 3 pgs. |
“U.S. Appl. No. 15/436,363, Non Final Office Action dated Oct. 9, 2018”, 15 pgs. |
“U.S. Appl. No. 15/436,363, Notice of Allowance dated Jan. 29, 2019”, 8 pgs. |
“U.S. Appl. No. 15/436,363, Response filed Nov. 28, 2018 to Non Final Office Action dated Oct. 9, 2018”, 15 pgs. |
“U.S. Appl. No. 15/437,018, Corrected Notice of Allowability dated Jul. 11, 2018”, 2 pgs. |
“U.S. Appl. No. 15/437,018, Corrected Notice of Allowance dated Jun. 6, 2018”, 5 pgs. |
“U.S. Appl. No. 15/437,018, Examiner Interview Summary dated Feb. 16, 2018”, 3 pgs. |
“U.S. Appl. No. 15/437,018, Non Final Office Action dated Jan. 26, 2018”, 9 pgs. |
“U.S. Appl. No. 15/437,018, Notice of Allowance dated May 18, 2018”, 7 pgs. |
“U.S. Appl. No. 15/437,018, Response Filed Mar. 21, 2018 to Non Final Office Action dated Jan. 26, 2018”, 9 pgs. |
“U.S. Appl. No. 15/492,089, Corrected Notice of Allowability dated May 24, 2019”, 2 pgs. |
“U.S. Appl. No. 15/492,089, Non Final Office Action dated Jan. 25, 2019”, 7 pgs. |
“U.S. Appl. No. 15/492,089, Notice of Allowance dated Apr. 4, 2019”, 9 pgs. |
“U.S. Appl. No. 15/492,089, Response filed Feb. 26, 2019 to Non Final Office Action dated Jan. 25, 2019”, 11 pgs. |
“U.S. Appl. No. 15/591,887, Corrected Notice of Allowance dated Sep. 8, 2017”, 4 pgs. |
“U.S. Appl. No. 15/591,887, Notice of Allowance dated Aug. 25, 2017”, 10 pgs. |
“U.S. Appl. No. 15/591,887, Preliminary Amendment filed Jun. 12, 2017”, 10 pgs. |
“U.S. Appl. No. 15/591,887, PTO Response to Rule 312 Communication dated Sep. 19, 2017”, 2 pgs. |
“U.S. Appl. No. 15/706,074, Final Office Action dated May 10, 2019”, 28 pgs. |
“U.S. Appl. No. 15/706,074, Non Final Office Action dated Nov. 7, 2018”, 26 pgs. |
“U.S. Appl. No. 15/706,074, Response filed Mar. 28, 2019 to Non Final Office Action dated Nov. 7, 2018”, 14 pgs. |
“U.S. Appl. No. 15/830,965, Corrected Notice of Allowability dated Aug. 6, 2018”, 4 pgs. |
“U.S. Appl. No. 15/830,965, Non Final Office Action dated Feb. 16, 2018”, 7 pgs. |
“U.S. Appl. No. 15/830,965, Notice of Allowability dated Jul. 5, 2018”, 5 pgs. |
“U.S. Appl. No. 15/830,965, Notice of Allowance dated Jun. 13, 2018”, 8 pgs. |
“U.S. Appl. No. 15/830,965, Response filed May 16, 2018 to Non Final Office Action dated Feb. 16, 2018”, 10 pgs. |
“U.S. Appl. No. 15/971,566, Advisory Action dated Nov. 22, 2019”, 2 pgs. |
“U.S. Appl. No. 15/971,566, Final Office Action dated Jul. 16, 2019”, 9 pgs. |
“U.S. Appl. No. 15/971,566, Final Office Action dated Oct. 31, 2018”, 38 pgs. |
“U.S. Appl. No. 15/971,566, Non Final Office Action dated Feb. 12, 2019”, 12 pgs. |
“U.S. Appl. No. 15/971,566, Non Final Office Action dated Jun. 14, 2018”, 7 pgs. |
“U.S. Appl. No. 15/971,566, Notice of Allowability dated Apr. 13, 2020”, 2 pgs. |
“U.S. Appl. No. 15/971,566, Notice of Allowance dated Jan. 13, 2020”, 8 pgs. |
“U.S. Appl. No. 15/971,566, Response filed Jan. 31, 2019 to Final Office Action dated Oct. 31, 2018”, 12 pgs. |
“U.S. Appl. No. 15/971,566, Response filed Jun. 12, 2019 to Non Final Office Action dated Feb. 12, 2019”, 11 pgs. |
“U.S. Appl. No. 15/971,566, Response filed Oct. 15, 2018 to Non Final Office Action dated Jun. 14, 2018”, 11 pgs. |
“U.S. Appl. No. 15/971,566, Response filed Nov. 15, 2019 to Final Office Action dated Jul. 16, 2019”, 13 pgs. |
“U.S. Appl. No. 16/014,193, Corrected Notice of Allowability dated Jan. 28, 2020”, 2 pgs. |
“U.S. Appl. No. 16/014,193, Non Final Office Action dated Jun. 28, 2019”, 22 pgs. |
“U.S. Appl. No. 16/014,193, Notice of Allowance dated Nov. 27, 2019”, 5 pgs. |
“U.S. Appl. No. 16/014,193, Response filed Aug. 22, 2019 to Non-Final Office Action dated Jun. 28, 2019”, 12 pgs. |
“U.S. Appl. No. 16/135,849, Preliminary Amendment filed Oct. 15, 2018”, 10 pgs. |
“U.S. Appl. No. 16/136,849, Corrected Notice of Allowability dated Apr. 25, 2019”, 4 pgs. |
“U.S. Appl. No. 16/136,849, Non Final Office Action dated Oct. 17, 2018”, 4 pgs. |
“U.S. Appl. No. 16/136,849, Notice of Allowance dated Mar. 5, 2019”, 7 pgs. |
“U.S. Appl. No. 16/136,849, Response filed Jan. 17, 2019 to Non Final Office Action dated Oct. 17, 2018”, 9 pgs. |
“U.S. Appl. No. 16/265,382, Non Final Office Action dated Mar. 3, 2020”, 18 pgs. |
“U.S. Appl. No. 16/277,626, Examiner Interview Summary dated Apr. 7, 2020”, 3 pgs. |
“U.S. Appl. No. 16/277,626, Final Office Action dated Feb. 22, 2021”, 18 pgs. |
“U.S. Appl. No. 16/277,626, Final Office Action dated May 18, 2020”, 30 pgs. |
“U.S. Appl. No. 16/277,626, Final Office Action dated Aug. 10, 2020”, 35 pgs. |
“U.S. Appl. No. 16/277,626, Final Office Action dated Aug. 20, 2021”, 24 pgs. |
“U.S. Appl. No. 16/277,626, Non Final Office Action dated Mar. 24, 2020”, 28 pgs. |
“U.S. Appl. No. 16/277,626, Non Final Office Action dated Jul. 12, 2021”, 20 pgs. |
“U.S. Appl. No. 16/277,626, Non Final Office Action dated Jul. 13, 2020”, 34 pgs. |
“U.S. Appl. No. 16/277,626, Non Final Office Action dated Nov. 29, 2021”, 19 pgs. |
“U.S. Appl. No. 16/277,626, Non Final Office Action dated Nov. 30, 2020”, 19 pgs. |
“U.S. Appl. No. 16/277,626, Response filed Jan. 28, 2021 to Non Final Office Action dated Nov. 30, 2020”, 9 pgs. |
“U.S. Appl. No. 16/277,626, Response filed Apr. 28, 2020 to Non Final Office Action dated Mar. 24, 2020”, 12 pgs. |
“U.S. Appl. No. 16/277,626, Response filed May 11, 2021 to Final Office Action dated Feb. 22, 2021”, 10 pgs. |
“U.S. Appl. No. 16/277,626, Response filed May 29, 2020 to Final Office Action dated May 18, 2020”, 12 pgs. |
“U.S. Appl. No. 16/277,626, Response filed Jul. 16, 2020 to Non Final Office Action dated Jul. 13, 2020”, 10 pgs. |
“U.S. Appl. No. 16/277,626, Response filed Aug. 10, 2021 to Non Final Office Action dated Jul. 12, 2021”, 9 pgs. |
“U.S. Appl. No. 16/277,626, Response filed Aug. 19, 2020 to Final Office Action dated Aug. 10, 2020”, 10 pgs. |
“U.S. Appl. No. 16/277,626, Response filed Oct. 21, 2021 to Final Office Action dated Aug. 20, 2021”, 11 pgs. |
“U.S. Appl. No. 16/433,793, Final Office Action dated Apr. 30, 2021”, 9 pgs. |
“U.S. Appl. No. 16/433,793, Non Final Office Action dated Jan. 21, 2021”, 26 pgs. |
“U.S. Appl. No. 16/433,793, Notice of Allowance dated Aug. 6, 2021”, 14 pgs. |
“U.S. Appl. No. 16/433,793, Response filed Apr. 21, 2021 to Non Final Office Action dated Jan. 21, 2021”, 12 pgs. |
“U.S. Appl. No. 16/433,793, Response filed Jun. 30, 2021 to Final Office Action dated Apr. 30, 2021”, 9 pgs. |
“U.S. Appl. No. 16/438,226, Corrected Notice of Allowability dated May 1, 2020”, 4 pgs. |
“U.S. Appl. No. 16/438,226, Final Office Action dated Jan. 3, 2020”, 10 pgs. |
“U.S. Appl. No. 16/438,226, Non Final Office Action dated Jul. 10, 2019”, 6 pgs. |
“U.S. Appl. No. 16/438,226, Notice of Allowance dated Mar. 26, 2020”, 8 pgs. |
“U.S. Appl. No. 16/438,226, Response filed Mar. 16, 2020 to Final Office Action dated Jan. 3, 2020”, 11 pgs. |
“U.S. Appl. No. 16/438,226, Response filed Oct. 8, 2019 to Non-Final Office Action dated Jul. 10, 2019”, 11 pgs. |
“U.S. Appl. No. 16/749,678, Final Office Action dated May 13, 2021”, 17 pgs. |
“U.S. Appl. No. 16/749,678, Non Final Office Action dated Jan. 22, 2021”, 19 pgs. |
“U.S. Appl. No. 16/749,678, Notice of Allowance dated Jul. 26, 2021”, 8 pgs. |
“U.S. Appl. No. 16/749,678, Response filed Apr. 21, 2021 to Non Final Office Action dated Jan. 22, 2021”, 10 pgs. |
“U.S. Appl. No. 16/749,678, Response filed Jul. 13, 2021 to Final Office Action dated May 13, 2021”, 8 pgs. |
“U.S. Appl. No. 16/824,297, Notice of Allowance dated Dec. 30, 2020”, 9 pgs. |
“U.S. Appl. No. 16/824,297, Supplemental Notice of Allowability dated Jan. 25, 2021”, 2 pgs. |
“U.S. Appl. No. 16/824,297, Supplemental Notice of Allowability dated Feb. 18, 2021”, 2 pgs. |
“U.S. Appl. No. 16/913,503, 312 Amendment filed Mar. 23, 2022”, 9 pgs. |
“U.S. Appl. No. 16/913,503, Notice of Allowance dated Dec. 23, 2021”, 8 pgs. |
“U.S. Appl. No. 16/913,503, PTO Response to Rule 312 Communication dated Apr. 1, 2022”, 2 pgs. |
“U.S. Appl. No. 17/248,833, Non Final Office Action dated Sep. 30, 2021”, 8 pgs. |
“BlogStomp”, StompSoftware, [Online] Retrieved from the Internet: <URL: http://stompsoftware.com/blogstomp>, (accessed May 24, 2017), 12 pgs. |
“Chinese Application Serial No. 201680035045, Response filed Jul. 6, 2021 to Office Action dated Mar. 24, 2021”, w/ English Claims, 51 pgs. |
“Chinese Application Serial No. 201680035045.X, Office Action dated Mar. 24, 2021”, w/o English Translation, 19 pgs. |
“Chinese Application Serial No. 201680035045.X, Office Action dated Aug. 5, 2020”, w/English Translation, 11 pgs. |
“Chinese Application Serial No. 201680035045.X, Office Action dated Sep. 10, 2021”, w/English Translation, 26 pgs. |
“Chinese Application Serial No. 201680035045.X, Response filed Nov. 29, 2021 to Office Action dated Sep. 10, 2021”, w/English Claims, 18 pgs. |
“Chinese Application Serial No. 201680035045.X, Response filed Dec. 18, 2020 to Office Action dated Aug. 5, 2020”, w/ English Claims, 50 pgs. |
“Cup Magic Starbucks Holiday Red Cups come to life with AR app”, Blast Radius, [Online] Retrieved from the Internet: <URL: https://web.archive.org/web/20160711202454/http://www.blastradius.com/work/cup-magic>, (2016), 7 pgs. |
“Daily App: InstaPlace (iOS/Android): Give Pictures a Sense of Place”, TechPP, [Online] Retrieved from the Internet: <URL: http://techpp.com/2013/02/15/instaplace-app-review>, (2013), 13 pgs. |
“Deltatre and Vizrt expanding partnership for Magma Pro Football solution”, Vizrt, [Online] Retrieved from the Internet: <URL: http://www.vizrt.com/news/newsgrid/39609/deltatre_and_Vizrt_expanding_partnership_for_Magma_Pro_Football_solution>, (2013), 5 pgs. |
“European Application Serial No. 16795488.2, Communication Pursuant to Article 94(3) EPC dated Jun. 30, 2021”, 6 pgs. |
“European Application Serial No. 16795488.2, Communication Pursuant to Article 94(3) EPC dated Nov. 11, 2020”, 6 pgs. |
“European Application Serial No. 16795488.2, Response filed Mar. 22, 2021 to Communication Pursuant to Article 94(3) EPC dated Nov. 11, 2020”, 23 pgs. |
“European Application Serial No. 16795488.2, Response filed Dec. 7, 2018 to Communication Pursuant to Rules 161(1) and 162 EPC dated Jun. 7, 2018”, w/ English Claims, 114 pgs. |
“InstaPlace Photo App tell The Whole Story”, [Online] Retrieved from the Internet: <URL: youtu.be/uF_gFkg1hBM>, (Nov. 8, 2013), 113 pgs., 1:02 min. |
“International Application Serial No. PCT/US2015/037251, International Search Report dated Sep. 29, 2015”, 2 pgs. |
“International Application Serial No. PCT/US2016/059503, International Preliminary Report on Patentability dated May 11, 2018”, 7 pgs. |
“International Application Serial No. PCT/US2016/059503, International Search Report dated Jan. 23, 2017”, 4 pgs. |
“International Application Serial No. PCT/US2016/059503, Written Opinion dated Jan. 23, 20 17”, 5 pgs. |
“Introducing Snapchat Stories”, [Online] Retrieved from the Internet: <URL: https://web.archive.org/web/20131026084921/https://www.youtube.com/watch?v=88Cu3yN-LIM>, (Oct. 3, 2013), 92 pgs.; 00:47 min. |
“Korean Application Serial No. 16-2017-7035785, Notice of Preliminary Rejection dated Dec. 28, 2018”, w/ English Translation, 10pgs. |
“Korean Application Serial No. 10-2017-7035785, Response filed Mar. 12, 2019 to Notice of Preliminary Rejection dated Dec. 28, 2018”, w/ English Claims, 25 pgs. |
“Korean Application Serial No. 10-2019-7035272, Notice of Preliminary Rejection dated Feb. 5, 2020”, w/ English Translation, 9 pgs. |
“Korean Application Serial No. 10-2019-7035272, Response filed May 4, 2020 to Notice of Preliminary Rejection dated Feb. 5, 2020”, w/ English Claims, 21 pgs. |
“Macy's Believe-o-Magic”, [Online] Retrieved from the Internet: <URL: https://web.archive.org/web/20190422101854/https://www.youtube.com/watch?v=xvzRXy3J0Z0&feature-youtu.be<, (Nov. 7, 2011), 102 pgs.; 00:51 min. |
“Macy's introduces Augmented Reality Experience in Stores across Country as Part of Its 2011 Believe Campaign”, Business Wire, [Online] Retrieved from the Internet: <URL: https://www.businesswire.com/news/home/20111102006759/en/Macys-Introduces-Augmented-Reallty-Experience-Stores-Country>, (Nov. 2, 2011), 6 pgs. |
“Starbucks Cup Magic”, [Online] Retrieved from the Internet: <URL: https://www.youtube.com/watch?v=RWwQXi9RG0w>, (Nov. 8, 2011), 87 pgs.; 00:47 min. |
“Starbucks Cup Magic for Valentine's Day”, [Online] Retrieved from the Internet: <URL: https://www.youtube.com/watch?v=8nvqOzjq10w>, (Feb. 6, 2012), 88pgs.; 00:45 min. |
“Starbucks Holiday Red Cups Come to Life, Signaling the Return of the Merriest Season”, Business Wire, [Online] Retrieved from the Internet: <URL: http://www.businesswire.com/news/home/20111115005744/en/2479513/Starbucks-Holiday-Red-Cups-Life-Signaling-Returns, (Nov. 15, 2011), 5 pgs. |
Carthy, Roi, “Dear All Photo Apps: Mobil Just Won Filters”, TechCrunch, [Online] Retrieved from the Internet: <URL: https://techcrunch.com/2011/09/08/mobli-filters>, (Sep. 8, 2011), 10 pgs. |
Castelluccia, Claude, et al., “EphPub: Toward robust Ephemeral Publishing”, 19th IEEE International Conference on Network Protocols (ICNP), (Oct. 17, 2011), 18 pgs. |
Fajman, “An Extensible Message Format for Message Disposition Notifications”, Request for Comments: 2298, National Institutes of Health, (Mar. 1998), 28 pgs. |
Janthong, Isaranu, “Instaplace ready on Android Google Play store”, Android App Review Thailand, [Online] Retrieved from the Internet: <URL: http://www.android-free-app-review.com/2013/01/instaplace-androld-google-play-store.html>, (Jan. 23, 2013), 9 pgs. |
Klein, Georg, “Parallel Tracking and Mapping for Small AR Workspaces—Source Code”, PTAM Blog, [Online] Retrieved from the Internet on Apr. 3, 2019: <URL: www.robots.ox.ac.uk/˜gk/PTAM/, (Feb. 2014), 2 pgs. |
Leyden, John, “This SMS will self-destruct in 40 seconds”, [Online] Retrieved from the Internet: <URL: http://www.theregister.co.uk/2005/12/12/stealthtext/>, (Dec. 12, 2005), 1 pg. |
MacLeod, Duncan, “Macys Believe-o-Magic App”, [Online] Retrieved from the Internet: <URL: http://theinspirationroom.com/daily/2011/macys-believe-o-magic-app>, (Nov. 14, 2011), 10 pgs. |
MacLeod, Duncan, “Starbucks Cup Magic Lets Merry”, [Online] Retrieved from the Internet: <URL: http://theinspirationroom.com/daily/2011/starbucks-cup-magic>, (Nov. 12, 2011), 8 pgs. |
Maher, Mary Lou, et al., “Designworld: An Augmented 3D Virtual World for Multidisciplinary, Collaborative Design”, University of Sydney, Key Centre for Design Computing and Cognition, (2006), 10 pgs. |
Melanson, Mike, “This text message will self destruct in 60 seconds”, [Online] Retrieved from the Internet: <URL: http://readwrite.com/2011/02/T1/this_text_message_will_self_destruct_in_60_seconds>, (Feb. 18, 2015), 4 pgs. |
Nahar, Prakhar, et al., “Autonomous UAV Forced Graffiti Detection and Removal System Based on Machine Learning”, IEEE 2017 SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI, (2017), 8pgs. |
Narhare, Ashwini D, et al., “Trademark detection using SIFT features matching”, IEEE 2015 International Conference on Computing Communication Control and Automation, (2015), 684-688. |
Notopoulos, Katie, “A Guide To The New Snapchat Filters And Big Fonts”, [Online] Retrieved from the Internet: <URL: https://www.buzzfeed.com/katienotopoulos/a-guide-to-the-new-snapchat-filters-and-big-fonts?utm_term=.bkQ9qVZWe#.nv58YXpkV>, (Dec. 22, 2013), 13 pgs. |
Panzarino, Matthew, “Snapchat Adds Filters, A Replay Function And For Whatever Reason, Time, Temperature And Speed Overlays”, TechCrunch, [Online] Retrieved form the Internet: <URL: https://techcrunch.com/2013/12/20/snapchat-adds-filters-new-font-and-for-some-reason-time-temperature-and-speed-overlays/>, (Dec. 20, 2013), 12 pgs. |
Rosten, Edward, “FAST Corner Detection”, Edwardrosten.com, [Online] Retrieved from the Internet on Apr. 3, 2019: <URL: https://www.edwardrosten.com/work/fast.html>, (Feb. 25, 2018), 5 pgs. |
Sawers, Paul, “Snapchat for iOS Lets You Send Photos to Friends and Set How long They're Visible For”, [Online] Retrieved from the Internet: <URL: https://thenextweb.com/apps/2012/05/07/snapchat-for-ios-lets-you-send-photos-to-friends-and-set-how-long-theyre-visible-for/> (May 7, 2012), 5 pgs. |
Sheikh, MD. Abdul Alim, et al., “Traffic Sign Detection and Classification using Colour Feature and Neural Network”, IEEE 2016 International Conference on Intelligent Control Power and Instrumentation (ICICPI), (2016), 307-311. |
Shein, Esther, “Ephemeral Data”, Communications of the ACM, vol. 56, No. 9, (Sep. 2013), 3 pgs. |
Tripathi, Rohit, “Watermark Images in PHP And Save File on Server”, [Online] Retrieved from the Internet: <URL: http://code.rohitink.com/2012/12/28/watermark-images-in-php-and-save-file-on-servers, (Dec. 28, 2012), 4 pgs. |
Vaas, Lisa, “StealthText, Should You Choose to Accept it”, [Online] Retrieved from the Internet: <URL: http://www.eweek.com/print/c/a/MessagingandCollaboration/StealthTextShouldYouChoosetoAcceptIt>, (Dec. 13, 2005), 2 pgs. |
Wagner, Daniel, et al., “Pose Tracking from Natural Features on Mobile Phones”, Proc. of the 7th IEEE/ACM Intl. Symposium on Mixed and Augmented Reality, IEEE Computer Society, (2008), 10 pgs. |
Wei, Guan, “Hybrid methods for robust image matching and its applications in augmented reality”, PhD diss., University of Southern California, (2014), 131 pgs. |
“U.S. Appl. No. 16/277,626, Notice of Allowance dated Feb. 9, 2023”, 10 pgs. |
“Chinese Application Serial No. 201680035045.X, Response filed Dec. 21, 2022 to Office Action dated Oct. 10, 2022”, w/ English Claims, 51 pgs. |
“U.S. Appl. No. 17/474,392, Non Final Office Action dated Mar. 16, 2023”, 29 pgs. |
“U.S. Appl. No. 17/474,392, Response filed Mar. 24, 2023 to Non Final Office Action dated Mar. 16, 2023”, 8 pgs. |
“U.S. Appl. No. 17/474,392, Notice of Allowance dated Apr. 26, 2023”, 7 pgs. |
“U.S. Appl. No. 17/528,981, Non Final Office Action dated Jun. 29, 2023”, 15 pgs. |
“U.S. Appl. No. 17/856,720, Non Final Office Action dated Jul. 19, 2023”, 30 pgs. |
Number | Date | Country | |
---|---|---|---|
20220245907 A1 | Aug 2022 | US |
Number | Date | Country | |
---|---|---|---|
62248706 | Oct 2015 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 16913503 | Jun 2020 | US |
Child | 17728553 | US | |
Parent | 16438226 | Jun 2019 | US |
Child | 16913503 | US | |
Parent | 16136849 | Sep 2018 | US |
Child | 16438226 | US | |
Parent | 15830965 | Dec 2017 | US |
Child | 16136849 | US | |
Parent | 15591887 | May 2017 | US |
Child | 15830965 | US | |
Parent | 14954090 | Nov 2015 | US |
Child | 15591887 | US |