Patent Grant
11195018
Embodiments of the present disclosure relate generally to mobile computing technology and, more particularly, but not by way of limitation, to the presentation of augmented and virtual reality displays.
Augmented reality (AR) is a live direct or indirect view of a physical, real-world environment whose elements are supplemented, or “augmented.” by a computer-generated sensory input such as sound, video, graphics, or the like. As a result, the technology functions to enhance a user's perception of reality.
To easily identify the discussion of any particular element or act, the most significant digit or digits in a reference number refer to the figure number in which that element is first introduced.
Reference will now be made in detail to specific example embodiments for carrying out the inventive subject matter of the present disclosure. In the following description, specific details are set forth in order to provide a thorough understanding of the subject matter. It shall be appreciated that embodiments may be practiced without some or all of these specific details.
Disclosed are augmented reality (AR) personalization systems to enable a user to edit and personalize presentations of real-world typography in real-time. In other words, various embodiments allow text in a picture or video captured by a phone to be automatically analyzed to allow simple user editing of the text. The analysis and editing features allow the edited picture or video to maintain the look and feel of the original. In some embodiments, networked features allow one user to edit text on a sign at a particular location on first device and share those edits. A second user capturing an image of the sign using the AR personalized system will see the text edits from the first user displayed on the screen of the second device. Users viewing a sign at the same time through AR displays can see real-time updates and text edits as they are made by other users.
The AR personalization system captures an image depicting a physical location via a camera coupled to a client device. For example, the client device may be a mobile device that includes a camera configured to record and display images (e.g., photos, videos) in real-time. The AR personalization system causes display of the image at the client device, and scans the image to detect occurrences of typography within the image (e.g., signs, billboards, posters, graffiti). For example, the image may include a stop-sign. The AR personalization system may detect the text string displayed on the stop-sign that reads “STOP.”
In some example embodiments, in response to detection of typography within an image, the AR personalization system identifies properties of the typography. The AR personalization system may employ Natural Feature Tracking (NFT) techniques to identify locations of the occurrences of typography. The properties of the typography may for example include a set of characters, a height of the text, a length of the text, and a number of characters in the text, as well as a location of the text in the image, a color of the text, an opacity of the text, and in some embodiments a typeface, a font (e.g., a size, weight, and style of the typeface), or that the typeface is serif or sans serif. Using the stop-sign example above, the AR personalization system may determine features such as: a relative size of the typography in the image based on properties of the image that the character-set of the text string includes the letters “S,” “T,” “O,” and “P,”; that the characters of the text string are white; and that the characters of the text string are sans serif (or that they are “Ariel Narrow”).
In further embodiments, the AR typography personalization system identifies background patterns in which the typography may be overlaid or displayed upon. Background patterns may include solid colors (e.g., red, blue, orange), textile patterns (e.g., check, tartan, gingham), as well as features of an environment depicted in the image (e.g., bricks on a brick wall, trees, bushes, concrete, asphalt, clouds, etc.). Continuing with the stop-sign example discussed above, the AR personalization system may determine that the background of the typography is a solid red color.
The AR personalization system may receive a request to alter, modify, or personalize the occurrences of typography detected in the image. The request may include a user input selecting an occurrence of typography in the image, received from a client device. For example, a user viewing a presentation of the image at the client device may select the occurrence of typography in the image, and in response the AR personalization system may overlay a text field at a position on the occurrence of typography to receive text inputs over the occurrence of typography in the image. For example, the AR personalization system identifies tracking indicia that include features of an environment or active light sources in proximity to annotated objects within the environment (e.g., the ground's plane, or the horizon). Based on the positions of three or more known features in the environment, the AR personalization system generates and causes display of the text field over the occurrence of typography. Thus, as the user moves to different perspectives, the text field (and ultimately the altered typography) may remain in a consistent position.
The user may provide user inputs into the text field to delete or otherwise alter characters in the text string. Continuing with the stop-sign example discussed above, the AR personalization may receive a user input selecting the typography of the stop-sign. In response to receiving the selection of the typography of the stop-sign, the AR personalization system causes display of a text field over the typography of the stop-sign.
The user may provide a user input into the text field to delete, change. or add to the one or more characters of the text string. For example, the user may alter the text string in the presentation of the image by deleting the “O” from the character-set and replacing it with an “A” and an “H.” The AR personalization system generates characters to display in the presentation of the image based on the properties of the text string, such as the size, color, and typeface. In response to receiving the user inputs modifying the text string, the AR personalization system updates the presentation of the image such that the text string displays as “STAHP” at the client device.
In some example embodiments, the AR personalization system provides functionality to tag the personalization requests to a particular occurrence of typography at one or more locations based factors including on geo-location coordinates, as well as properties of the typography. For example a user may tag a personalization request to alter/personalize all occurrences of a text string that includes certain properties (e.g., a character-set, a location, a background, etc.) detected by the AR personalization system, or alter/personalize a presentation of a specific occurrence of typography based on location data at multiple client devices.
For example, a user may create a personalization request for a specific word or phrase (e.g., “STAR WARS.” “STOP.” “CAUTION”), wherein the specific word or phrase may appear at multiple different locations. Upon detecting an occurrence of the specific word or phrase, based on properties of the specific word or phrase (e.g., characters, positions of the characters), the AR personalization system may apply the personalization request to alter a presentation of the word or phrase, in real-time.
The personalization request may include geolocation coordinates, as well as user identifiers of a set of users authorized to view the personalized typography. For example, a user may generate a personalization request that includes personalized typography, geolocation coordinates, an indication of an occurrence of typography to alter in a presentation, and a set of user identifiers. Upon detecting users identified by the user identifiers at the location specified by the geolocation coordinates, the AR personalization system alters a presentation of the occurrence of typography displayed at their corresponding user devices to include the personalization request. For example, a user may generate a personalization request to alter a presentation of an occurrence of typography (e.g., a movie poster). The personalization request includes an indication of the occurrence of typography, changes to be made to the occurrence of typography (e.g., a character or string of characters to add), geolocation coordinates, as well as a list of user identifiers that includes user identifier X. For example, a user may select the occurrence of typography within the presentation, and in response, the AR personalization system may apply NFT systems to identify features within the presentation to identify and mark the occurrence of typography. The user may provide the AR personalization system with a set of changes that include new characters to add to the occurrence of typography, as well as an indication of a position in which to place the changes in the presentation. The user identified by user identifier X may display a presentation of the occurrence of the text string at a corresponding client device. In response, the AR personalization system identifies the user and alters the presentation based on the personalization request.
Accordingly, each messaging client application 104 is able to communicate and exchange data with another messaging client application 104 and with the messaging server system 108 via the network 106. The data exchanged between messaging client applications 104, and between a messaging client application 104 and the messaging server system 108, includes functions (e.g., commands to invoke functions) as well as payload data (e.g., text, audio, video or other multimedia data which may include or be used as anamorphic media).
The messaging server system 108 provides server-side functionality via the network 106 to a particular messaging client application 104. While certain functions of the messaging system 100 are described herein as being performed by either a messaging client application 104 or by the messaging server system 108, it will be appreciated that the location of certain functionality either within the messaging client application 104 or the messaging server system 108 is a design choice. For example, it may be technically preferable to initially deploy certain technology and functionality within the messaging server system 108, but to later migrate this technology and functionality to the messaging client application 104 where a client device 102 has a sufficient processing capacity.
The messaging server system 108 supports various services and operations that are provided to the messaging client application 104. Such operations include transmitting data to, receiving data from, and processing data generated by the messaging client application 104. In some embodiments, this data includes, message content, client device information, geolocation information, media annotation and overlays, message content persistence conditions, social network information, and live event information, as examples. In other embodiments, other data is used. Any such data may be used as part of or to generate anamorphic media in accordance with different embodiments described herein. Data exchanges within the messaging system 100 are invoked and controlled through functions available via user interfaces (UIs) of the messaging client application 104.
Turning now specifically to the messaging server system 108, an Application Program Interface (API) server 110 is coupled to, and provides a programmatic interface to, an application server 112. The application server 112 is communicatively coupled to a database server(s) 118, which facilitates access to a database(s) 120 in which is stored data associated with messages processed by the application server 112.
Dealing specifically with the Application Program Interface (API) server 110, this server receives and transmits message data (e.g., commands and message payloads) between the client device 102 and the application server 112. Specifically, the Application Program Interface (API) server 110 provides a set of interfaces (e.g., routines and protocols) that can be called or queried by the messaging client application 104 in order to invoke functionality of the application server 112. The Application Program Interface (API) server 110 exposes various functions supported by the application server 112, including account registration, login functionality, the sending of messages, via the application server 112, from a particular messaging client application 104 to another messaging client application 104, the sending of media files (e.g., images or video) from a messaging client application 104 to the messaging server application 114, and for possible access by another messaging client application 104, the setting of a collection of media data (e.g., story), the retrieval of a list of friends of a user of a client device 102, the retrieval of such collections, the retrieval of messages and content, the adding and deletion of friends to a social graph, the location of friends within a social graph, opening and application event (e.g., relating to the messaging client application 104).
The application server 112 hosts a number of applications and subsystems, including a messaging server application 114, an image processing system 116, a social network system 122, and an typography personalization system 124. The messaging server application 114 implements a number of message processing technologies and functions, particularly related to the aggregation and other processing of content (e.g., textual and multimedia content) included in messages received from multiple instances of the messaging client application 104. As will be described in further detail, the text and media content from multiple sources may be aggregated into collections of content (e.g., called stories or galleries). These collections are then made available, by the messaging server application 114, to the messaging client application 104. Other processor and memory intensive processing of data may also be performed server-side by the messaging server application 114, in view of the hardware requirements for such processing.
The application server 112 also includes an image processing system 116 that is dedicated to performing various image processing operations, typically with respect to images or video received within the payload of a message at the messaging server application 114.
The social network system 122 supports various social networking functions services, and makes these functions and services available to the messaging server application 114. To this end, the social network system 122 maintains and accesses an entity graph 304 within the database(s) 120. Examples of functions and services supported by the social network system 122 include the identification of other users of the messaging system 100 with which a particular user has relationships or is “following,” and also the identification of other entities and interests of a particular user. The typography personalization system 124 provides functionality to identify and enable personalization of occurrences of typography identified in a presentation of an image at a client device (e.g., client device 102).
The application server 112 is communicatively coupled to one or more database server(s) 118, which facilitates access to a database(s) 120 in which is stored data associated with messages processed by the messaging server application 114.
The ephemeral timer system 202 is responsible for enforcing the temporary access to content permitted by the messaging client application 104 and the messaging server application 114. To this end, the ephemeral timer system 202 incorporates a number of timers that, based on duration and display parameters associated with a message, or collection of messages (e.g., a SNAPCHAT story), selectively display and enable access to messages and associated content such as anamorphic media via the messaging client application 104. Further details regarding the operation of the ephemeral timer system 202 are provided below.
The collection management system 204 is responsible for managing collections of media (e.g., collections of text, image video and audio data). In some examples, a collection of content (e.g., messages, including personalized typography, images, video, text and audio) may be organized into an “event gallery” or an “event story.” Such a collection may be made available for a specified time period, such as the duration of an event to which the content relates. For example, content such as personalized augmented reality typography displayed at specific locations based on geolocation coordinates and features of an environment may be made available as a “story” for the duration of a time period. The collection management system 204 may also be responsible for publishing an icon that provides notification of the existence of a particular collection to the user interface of the messaging client application 104.
The collection management system 204 furthermore includes a curation interface 208 that allows a collection manager to manage and curate a particular collection of content. For example, the curation interface 208 enables an event organizer to curate a collection of content relating to a specific event (e.g., delete inappropriate content or redundant messages). Additionally, the collection management system 204 employs machine vision (or image recognition technology) and content rules to automatically curate a content collection. In certain embodiments, compensation may be paid to a user for inclusion of user generated content into a collection. In such cases, the curation interface 208 operates to automatically make payments to such users for the use of their content.
The annotation system 206 provides various functions that enable a user to annotate or otherwise modify or edit media content associated with a message. For example, the annotation system 206 provides functions related to the generation and publishing of media overlays for messages processed by the messaging system 100. The annotation system 206 operatively supplies a media overlay (e.g., a SNAPCHAT filter) to the messaging client application 104 based on a geolocation of the client device 102. In another example, the annotation system 206 operatively supplies a media overlay to the messaging client application 104 based on other information, such as, social network information of the user of the client device 102. A media overlay may include audio and visual content and visual effects. Examples of audio and visual content include anamorphic media, pictures, texts, logos, animations, and sound effects. An example of a visual effect includes color overlaying, or projecting an anamorphic media item over a presentation depicting a space. The audio and visual content or the visual effects can be applied to a media content item (e.g., a photo) at the client device 102. For example, the media overlay including text that can be overlaid on top of a photograph or video stream generated taken by the client device 102. In another example, the media overlay includes an identification of a location overlay (e.g., Venice beach), a name of a live event, or a name of a merchant overlay (e.g., Beach Coffee House). In another example, the annotation system 206 uses the geolocation of the client device 102 to identify a media overlay that includes the name of a merchant at the geolocation of the client device 102. The media overlay may include other indicia associated with the merchant. The media overlays may be stored in the database(s) 120 and accessed through the database server(s) 118.
In one example embodiment, the annotation system 206 provides a user-based publication platform that enables users to select a geolocation on a map, and upload content associated with the selected geolocation. The user may also specify circumstances under which a particular media overlay should be offered to other users. The annotation system 206 generates a media overlay that includes the uploaded content and associates the uploaded content with the selected geolocation.
In another example embodiment, the annotation system 206 provides a merchant-based publication platform that enables merchants to select a particular media overlay associated with a geolocation via a bidding process. For example, the annotation system 206 associates the media overlay of a highest bidding merchant with a corresponding geolocation for a predefined amount of time
The database(s) 120 includes message data stored within a message table 314. The entity table 302 stores entity data, including an entity graph 304. Entities for which records are maintained within the entity table 302 may include individuals, corporate entities, organizations, objects, places, events etc. Regardless of type, any entity regarding which the messaging server system 108 stores data may be a recognized entity. Each entity is provided with a unique identifier, as well as an entity type identifier (not shown).
The entity graph 304 furthermore stores information regarding relationships and associations between entities. Such relationships may be social, professional (e.g., work at a common corporation or organization) interested-based or activity-based, merely for example.
The database(s) 120 also stores annotation data, in the example form of filters, in an annotation table 312. Filters for which data is stored within the annotation table 312 are associated with and applied to videos (for which data is stored in a video table 310) and/or images (for which data is stored in an image table 308). Filters, in one example, are overlays (e.g., anamorphic media items) that are displayed as overlaid on an image or video during presentation to a recipient user. For example, the overlay may include an anamorphic media item displayed within a presentation of a space, such that the anamorphic media item appears to be projected over a set of three dimensional surfaces of a space, following the contours of the surfaces of the space. Filters may be of varies types, including a user-selected filters from a gallery of filters presented to a sending user by the messaging client application 104 when the sending user is composing a message. Other types of filers include geolocation filters (also known as geo-filters) which may be presented to a sending user based on geographic location. For example, geolocation filters specific to a neighborhood or special location may be presented within a user interface by the messaging client application 104, based on geolocation information determined by a GPS unit of the client device 102. Another type of filer is a data filer, which may be selectively presented to a sending user by the messaging client application 104, based on other inputs or information gathered by the client device 102 during the message creation process. Example of data filters include current temperature at a specific location, a current speed at which a sending user is traveling, battery life for a client device 102 or the current time.
Other annotation data that may be stored within the image table 308 is so-called “lens” data. A “lens” may be a real-time special effect and sound that may be added to an image or a video.
As mentioned above, the video table 310 stores video data which, in one embodiment, is associated with messages for which records are maintained within the message table 314. Similarly, the image table 308 stores image data associated with messages for which message data is stored in the entity table 302. The entity table 302 may associate various annotations from the annotation table 312 with various images and videos stored in the image table 308 and the video table 310.
A story table 306 stores data regarding collections of messages and associated image, video or audio data, which are compiled into a collection (e.g., a SNAPCHAT story or a gallery). The creation of a particular collection may be initiated by a particular user (e.g., each user for which a record is maintained in the entity table 302) A user may create a “personal story” in the form of a collection of content that has been created and sent/broadcast by that user. To this end, the user interface of the messaging client application 104 may include an icon that is user selectable to enable a sending user to add specific content to his or her personal story.
A collection may also constitute a “live story,” which is a collection of content from multiple users that is created manually, automatically or using a combination of manual and automatic techniques. For example, a “live story” may constitute a curated stream of user-submitted content from varies locations and events. Users, whose client devices have location services enabled and are at a common location event at a particular time may, for example, be presented with an option, via a user interface of the messaging client application 104, to contribute content to a particular live story. The live story may be identified to the user by the messaging client application 104, based on his or her location. The end result is a “live story” told from a community perspective.
A further type of content collection is known as a “location story,” which enables a user whose client device 102 is located within a specific geographic location (e.g., on a college or university campus) to contribute to a particular collection. In some embodiments, a contribution to a location story may require a second degree of authentication to verify that the end user belongs to a specific organization or other entity (e.g., is a student on the university campus).
The contents (e.g. values) of the various components of message 400 may be pointers to locations in tables within which content data values are stored. For example, an image value in the message image payload 406 may be a pointer to (or address of) a location within an image table 308. Similarly, values within the message video payload 408 may point to data stored within a video table 310, values stored within the message annotations 412 may point to data stored in an annotation table 312, values stored within the message story identifier 418 may point to data stored in a story table 306, and values stored within the message sender identifier 422 and the message receiver identifier 424 may point to user records stored within an entity table 302.
Any one or more of the modules described may be implemented using hardware alone (e.g., one or more of the processors 508 of a machine) or a combination of hardware and software. For example, any module described of the typography personalization system 124 may physically include an arrangement of one or more of the processors 508 (e.g., a subset of or among the one or more processors of the machine) configured to perform the operations described herein for that module. As another example, any module of the typography personalization 124 may include software, hardware, or both, that configure an arrangement of one or more processors 508 (e.g., among the one or more processors of the machine) to perform the operations described herein for that module. Accordingly, different modules of the typography personalization system 124 may include and configure different arrangements of such processors 508 or a single arrangement of such processors 508 at different points in time. Moreover, any two or more modules of the typography personalization system 124 may be combined into a single module, and the functions described herein for a single module may be subdivided among multiple modules. Furthermore, according to various example embodiments, modules described herein as being implemented within a single machine, database, or device may be distributed across multiple machines, databases, or devices.
Operations 602 and 604 may be performed by the presentation module 502. At operation 602, the presentation module 502 captures an image depicting a physical location. For example, the client device 102 may include a camera element configured to record images of a physical location. The presentation module 502 may access the camera element of the client device 102 and generate an image based on the recorded images. For example, the image captured by the presentation module 502 may include video or still images.
At operation 604, the presentation module 502 analyzes the image to identify one or more occurrences of typography within the image. As discussed above, the image may depict a physical location, wherein the physical location includes one or more occurrences of typography. For example, the image may depict a street intersection that includes street signs, stop signs, billboards, as well as cars with license plates, that all include occurrences of typography. The occurrences of typography therefore could include text strings such as the word “STOP” on a stop sign, the letters and numbers of a license plate, as well as a word or phrase presented on a billboard. The occurrences of typography may also include corresponding background patterns. For example, in the case of a stop sign, the typography of the stop sign “STOP” is presented over a red background, while a logo painted on a brick wall would have a brick background.
Operation 606 may be performed by the identification module 504. At operation 606, the identification module 504 identifies properties of the occurrences of typography within the presentation of the images. The properties of the typography may for example include size (e.g., height, length, number of characters), location (i.e., where it is in the image), color, opacity, a character-set (i.e., the letters and numbers that make up the typography) and in some embodiments a typeface (or that the typeface is serif or sans serif).
In some example embodiments, the identification module 504 identifies positions of the occurrences of typography in the presentation of the image based on NFT techniques. For example, the identification module 504 may identify one or more features within the presentation and determines a relative position of the occurrences of typography relative to one another and in relation to the features.
In some example embodiments, the identification module 504 identifies a typeface and a font of the typeface, of an occurrence of typography. Having determined the front and the typeface of the occurrence of typography, the identification module 504 compares the font and the typeface against a catalogue of fronto-parallel views of fonts and typefaces to determine deformities of the occurrence of typography. Based on the deformities of the occurrence of typography, the identification module 504 may identify a position and geometry of a surface in which the occurrence of typography appears, in order to identify a shape of the surface.
For example, the identification module 504 identifies a typeface of the occurrence of typography based on properties of the text string. In response to identifying the typeface, the identification module 504 compares the text string against a set of characters from a catalogue of characters, based on the typeface (e.g., Times New Roman, Ariel, Wingdings, etc.), to identify evidence of distortion and deformities in the text string. Based on the distortion and deformities, the identifications module 504 determines a shape of a surface in which the text string appears.
Operations 608 and 610 may be performed by the presentation module 502. At operation 608, the presentation module 502 receives a personalization request to alter or edit one or more of the occurrences of typography identified in the presentation of the image. For example, the personalization request may include a request to remove one or more characters from a text string (e.g., the typography). In some example embodiments, the feature tracking module 506 generates and causes display of a text field to receive changes (e.g., deletions and additions) to the typography at positions overlaid upon the occurrences of typography. For example, the feature tracking module 506 may identify one or more features within the presentation, and generate and cause display of the text fields at positions within the presentation such that as the user moves, the text fields remain in their relative positions. The user may select one or more of the occurrences of typography and provide changes (e.g., additions, deletions) directly into the text field.
In some example embodiments, the personalization request may include a request to alter or change other feature of the occurrence of typography, beyond the typography itself. For example, a user may provide inputs specifying that a background color or pattern within the presentation be changed (e.g., change a red sign to a green sign). In further embodiments, the personalization request may include a request to add an image retrieved from a database to the presentation. For example, a user may access a database or repository of images that includes an image of a face, and specify a location within the presentation in which to add the image of the face. In this way, a user may alter or otherwise change elements within the presentation beyond simply the typography itself. For example, the personalization request may specify that all occurrences of the word “apple” identified within an image be replaced with a picture selected by the user (e.g., an image of an apple).
At operation 610, the presentation module 502 generates a presentation of the image, wherein the presentation of the image includes an updated text string based on the personalization request. In some example embodiments, the updated txt string may be presented based on the form of the surface identified by the identification module 504, based on deformities of the typeface. For example, one or more characters of the text string may be changed or removed from the image, and replaced with new characters, or simply filled in with the background pattern.
As an illustrative example, the occurrence of typography identified by the identification module 504 may include a billboard that includes an advertisement with a text string that reads “WINCHESTER MYSTERY HOUSE.” The identification module 504 identifies the text string, and a position of the text string in the presentation, and generates and causes display of a text field at the location of the text string (overlaid on top of the text string in the presentation of the image).
A user selects the text string and provides inputs directly into the text field to personalize the typography. The inputs may for example include: adding or deleting characters, changing colors of the typography, changing a typeface of the typography, translating the typography into a different language (e.g., English to Chinese), and changing a size of the typography. For example, the user may change or delete one or more characters of the text string (“WINCHESTER MYSTERY HOUSE”) such that the presentation displays the text string as “WINCHESTER MYSTERY MOUSE.” or anything else.
In some example embodiments, the typography personalization system 124 may identify and alter a presentation that includes the occurrence of typography, in response to the identification module 504 detecting the occurrence of typography based on attributes of the typography (e.g., a set of characters, a typeface, a color, an image among the characters, a logo, etc.). For example, a user may generate a personalization request that alters all occurrences of the word “EXIT” detected by the identification module 504, in real-time.
In further embodiments, the user may attach the personalization request to a message, wherein the message is deliverable to one or more client devices (e.g., a recipient), and the recipients of the message may similarly alter presentations of images that include the occurrence of typography of the personalization request. For example, the personalization request may be tagged to a specific word or phrase, such that when the identification module 504 detects the word or phrase, the presentation module 502 alters the presentation based on the personalization request.
In further embodiments, the personalization may be tied to a specific occurrence of typograph (e.g., a word or phrase), and a creator of the personalization request may alter the personalization request, such that presentations of the occurrence of typography displayed at recipient devices are altered in real time. For example, a creating user may create a personalization request for occurrences of the word “STOP,” and transmit the personalization request to a recipient. As the creating user alter the personalization request, displays of the word “STOP” at the recipient device may be altered by the presentation module 502, in real-time.
Operation 702 may be performed by the identification module 504. At operation 702, the identification module 504 retrieves location data of the physical location depicted by the image. For example, the identification module 504 may retrieve geolocation coordinates from the client device 102 in response to causing display of the image within the presentation at the client device 102. In some example embodiments, the identification module 504 may parse image data of the image to retrieve image metadata indicating a location in which the image was captured.
Operations 704 may be performed by the presentation module 502. At operation 704, the presentation module 502 geo-tags the personalization request received at operation 608 of
At operation 706, the identification module 504 detects a second client device at the physical location. For example, the typography personalization system 124 may generate and maintain a geofence that encompasses the location identified by the location data of the image, in response to geotagging the image with the personalization request. A geofence is a virtual geographic boundary, defined by Global Positioning Systems (GPS), WiFi, Radio-Frequency Identification (RFID), or Cellular systems, that enables systems to trigger a response when a device is detecting in proximity with, or transgressing a boundary of the geofence. A second client device may transgress a boundary of a geofence that encompasses the location and in response the identification module 504 may identify the second client device. In further embodiments, the presentation module 502 may receive an indication that the second client device has captured an image depicting the location to generate and cause display of a presentation of the image at the second client device.
In some example embodiments, the identification module 504 accesses a user profile associated with a user of the second client device to retrieve user profile data, in response to detecting the second client device at the physical location. For example, the user profile of the user may include user profile information including a name and username, as well as demographics details and other associated user profile information (e.g., “likes,” purchase behavior, a friend list, etc.).
Operation 708 may be performed by the presentation module 502. At operation 708, the presentation module 502 personalizes the presentation of the image captured by the second client device in response to detecting the second client device at the location. For example, the image may include the occurrence of typography referenced by the personalization request. In response to detecting the second client device at the location, and causing display of the presentation of the image, the presentation module 502 may personalize the occurrence of typography within the presentation based on the personalization request.
In some example embodiments, the presentation module 502 may personalize the presentation of the image based on the user profile data of the user associated with the client device. For example, the presentation module 502 may replace a text string in the image with a new text string based on user profile data of the user, such as a name of the user.
In some example embodiments, the personalization request may include access or viewing credentials that include user authorization criteria. For example, the personalization request may include a set of user identifiers, such that the typography personalization system 124 only personalizes presentation of an occurrence of typography based on the personalization request of users identified by the user identifiers in the personalization request.
As discussed in operation 604 of
In some example embodiments, the personalization request from the user may include a request to change a color or pattern of the stop sign depicted in the image 802. For example, the user may select the stop sign in the image 802, and in response, the identification module 504 may identify boundaries of the stop sign based on features of the image 802 in response to receiving the selection of the stop sign. For example, the identification module 504 may apply feature identification techniques to determine boundaries of the stop sign based on contrasting colors, or changes in pattern or texture. Upon detecting the boundaries of the stop sign, the typography personalization system 124 may prompt the user to specify a color or pattern in which to add to the stop sign. The user may thereby specify a new color (e.g., green), or in some embodiments, may select an image or pattern from a data repository, which the presentation module 502 may thereby apply to the background of the stop sign of the image 802.
As discussed in operation 604 of
In some example embodiments, the personalization request may include a request to “face-swap” the face 906A of
Software Architecture
In the example architecture of
The operating system 1002 may manage hardware resources and provide common services. The operating system 1002 may include, for example, a kernel 1022, services 1024 and drivers 1026. The kernel 1022 may act as an abstraction layer between the hardware and the other software layers. For example, the kernel 1022 may be responsible for memory management, processor management (e.g., scheduling), component management, networking, security settings, and so on. The services 1024 may provide other common services for the other software layers. The drivers 1026 are responsible for controlling or interfacing with the underlying hardware. For instance, the drivers 1026 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 depending on the hardware configuration.
The libraries 1020 provide a common infrastructure that is used by the applications 1016 and/or other components and/or layers. The libraries 1020 provide functionality that allows other software components to perform tasks in an easier fashion than to interface directly with the underlying operating system 1002 functionality (e.g., kernel 1022, services 1024 and/or drivers 1026). The libraries 1020 may include system libraries 1044 (e.g., C standard library) that may provide functions such as memory allocation functions, string manipulation functions, mathematical functions, and the like. In addition, the libraries 1020 may include API libraries 1046 such as media libraries (e.g., libraries to support presentation and manipulation of various media format such as MPREG4, H.264, MP3, AAC, AMR, JPG, PNG), graphics libraries (e.g., an OpenGL framework that may be used to render 2D and 3D in a graphic content on a display), database libraries (e.g., SQLite that may provide various relational database functions), web libraries (e.g., WebKit that may provide web browsing functionality), and the like. The libraries 1020 may also include a wide variety of other libraries 1048 to provide many other APIs to the applications 1016 and other software components/modules.
The frameworks/middleware 1018 (also sometimes referred to as middleware) provide a higher-level common infrastructure that may be used by the applications 1016 and/or other software components/modules. For example, the frameworks/middleware 1018 may provide various graphic user interface (GUI) functions, high-level resource management, high-level location services, and so forth. The frameworks/middleware 1018 may provide a broad spectrum of other APIs that may be utilized by the applications 1016 and/or other software components/modules, some of which may be specific to a particular operating system 1002 or platform.
The applications 1016 include built-in applications 1038 and/or third-party applications 1040. Examples of representative built-in applications 1038 may include, but are not limited to, a contacts application, a browser application, a book reader application, a location application, a media application, a messaging application, and/or a game application. Third-party applications 1040 may include an application developed using the ANDROID™ or IOS™ software development kit (SDK) by an entity other than the vendor of the particular platform, and may be mobile software running on a mobile operating system such as IOS™, ANDROID™, WINDOWS™ Phone, or other mobile operating systems. The third-party applications 1040 may invoke the API calls 1008 provided by the mobile operating system (such as operating system 1002) to facilitate functionality described herein.
The applications 1016 may use built in operating system functions (e.g., kernel 1022, services 1024 and/or drivers 1026), libraries 1020, and frameworks/middleware 1018 to create user interfaces to interact with users of the system. Alternatively, or additionally, in some systems interactions with a user may occur through a presentation layer, such as presentation layer 1014. In these systems, the application/component “logic” can be separated from the aspects of the application/component that interact with a user.
The machine 1100 may include processors 1104, memory memory/storage 1106, and I/O components 1118, which may be configured to communicate with each other such as via a bus 1102. The memory/storage 1106 may include a memory 1114, such as a main memory, or other memory storage, and a storage unit 1116, both accessible to the processors 1104 such as via the bus 1102. The storage unit 1116 and memory 1114 store the instructions 1110 embodying any one or more of the methodologies or functions described herein. The instructions 1110 may also reside, completely or partially, within the memory 1114, within the storage unit 1116, within at least one of the processors 1104 (e.g., within the processor's cache memory), or any suitable combination thereof, during execution thereof by the machine 1100. Accordingly, the memory 1114, the storage unit 1116, and the memory of processors 1104 are examples of machine-readable media.
The I/O components 1118 may 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 1118 that are included in a particular machine 1100 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 1118 may include many other components that are not shown in
In further example embodiments, the I/O components 1118 may include biometric components 1130, motion components 1134, environmental environment components 1136, or position components 1138 among a wide array of other components. For example, the biometric components 1130 may 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 1134 may include acceleration sensor components (e.g., accelerometer), gravitation sensor components, rotation sensor components (e.g., gyroscope), and so forth. The environment components 1136 may include, for example, illumination sensor components (e.g., photometer), temperature sensor components (e.g., one or more thermometer that detect ambient temperature), humidity sensor components, pressure sensor components (e.g., 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 sensors (e.g., gas detection sensors to detection 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 1138 may include location sensor components (e.g., a Global Position system (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 may be implemented using a wide variety of technologies. The I/O components 1118 may include communication components 1140 operable to couple the machine 1100 to a network 1132 or devices 1120 via coupling 1122 and coupling 1124 respectively. For example, the communication components 1140 may include a network interface component or other suitable device to interface with the network 1132. In further examples, communication components 1140 may 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 1120 may be another machine or any of a wide variety of peripheral devices (e.g., a peripheral device coupled via a Universal Serial Bus (USB)).
Moreover, the communication components 1140 may detect identifiers or include components operable to detect identifiers. For example, the communication components 1140 may 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 Universal Product Code (UPC) bar code, multi-dimensional bar codes such as Quick Response (QR) code. Aztec code, Data Matrix, Dataglyph, MaxiCode, PDF417, Ultra Code. UCC RSS-2D bar code, and other optical codes), or acoustic detection components (e.g., microphones to identify tagged audio signals). In addition, a variety of information may be derived via the communication components 1140, such as, location via Internet Protocol (IP) geo-location, location via Wi-Fi® signal triangulation, location via detecting a NFC beacon signal that may indicate a particular location, and so forth.
“ANAMORPHOSIS” in this context refers to distortions and transformations applied to a media items such as images and videos, such that the media items appear normal when viewed from a particular point or through a suitable viewing device, mirror, or lens.
“PERSPECTIVE” in this context refers to a viewing angle of a user at a particular location.
“CARRIER SIGNAL” in this context refers to any intangible medium that is capable of storing, encoding, or carrying instructions for execution by the machine, and includes digital or analog communications signals or other intangible medium to facilitate communication of such instructions. Instructions may be transmitted or received over the network using a transmission medium via a network interface device and using any one of a number of well-known transfer protocols.
“CLIENT DEVICE” in this context refers to any machine that interfaces to a communications network to obtain resources from one or more server systems or other client devices. A client device may be, but is not limited to, a mobile phone, desktop computer, laptop, portable digital assistants (PDAs), smart phones, tablets, ultra books, netbooks, laptops, multi-processor systems, microprocessor-based or programmable consumer electronics, game consoles, set-top boxes, or any other communication device that a user may use to access a network.
“COMMUNICATIONS NETWORK” in this context refers to one or more portions of a network that may 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, a network or a portion of a network may include a wireless or cellular network and the coupling 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 may 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.
“EMPHEMERAL MESSAGE” in this context refers to a message that is accessible for a time-limited duration. An ephemeral message may be a text, an image, a video and the like. The access time for the ephemeral message may be set by the message sender. Alternatively, the access time may be a default setting or a setting specified by the recipient. Regardless of the setting technique, the message is transitory.
“MACHINE-READABLE MEDIUM” in this context refers to a component, device or other tangible media 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)) and/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. 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., code) for execution by a machine, such that the instructions, when executed by one or more processors of the machine, cause the machine 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.
“COMPONENT” in this context refers to a device, physical entity or logic having boundaries defined by function or subroutine calls, branch points, application program interfaces (APIs), or other technologies that provide for the partitioning or modularization of particular processing or control functions. Components may be combined via their interfaces with other components to carry out a machine process. A component may be a packaged functional hardware unit designed for use with other components and a part of a program that usually performs a particular function of related functions. Components may constitute either software components (e.g., code embodied on a machine-readable medium) or hardware components. A “hardware component” is a tangible unit capable of performing certain operations and may 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 components of a computer system (e.g., a processor or a group of processors) may be configured by software (e.g., an application or application portion) as a hardware component that operates to perform certain operations as described herein. A hardware component may also be implemented mechanically, electronically, or any suitable combination thereof. For example, a hardware component may include dedicated circuitry or logic that is permanently configured to perform certain operations. A hardware component may be a special-purpose processor, such as a Field-Programmable Gate Array (FPGA) or an Application Specific Integrated Circuit (ASIC). A hardware component may also include programmable logic or circuitry that is temporarily configured by software to perform certain operations. For example, a hardware component may include software executed by a general-purpose processor or other programmable processor. Once configured by such software, hardware components 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 component mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations. Accordingly, the phrase “hardware component” (or “hardware-implemented component”) 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. Considering embodiments in which hardware components are temporarily configured (e.g., programmed), each of the hardware components need not be configured or instantiated at any one instance in time. For example, where a hardware component 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 components) at different times. Software accordingly configures a particular processor or processors, for example, to constitute a particular hardware component at one instance of time and to constitute a different hardware component at a different instance of time. Hardware components can provide information to, and receive information from, other hardware components. Accordingly, the described hardware components may be regarded as being communicatively coupled. Where multiple hardware components exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) between or among two or more of the hardware components. In embodiments in which multiple hardware components are configured or instantiated at different times, communications between such hardware components may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware components have access. For example, one hardware component may perform an operation and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware component may then, at a later time, access the memory device to retrieve and process the stored output. Hardware components may 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 may 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 may constitute processor-implemented components that operate to perform one or more operations or functions described herein. As used herein, “processor-implemented component” refers to a hardware component implemented using one or more processors. Similarly, the methods described herein may 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 may be performed by one or more processors or processor-implemented components. 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 Application Program Interface (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 components may 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 components may be distributed across a number of geographic locations.
“PROCESSOR” in this context refers to any circuit or virtual circuit (a physical circuit emulated by logic executing on an actual processor) that manipulates data values according to control signals (e.g., “commands”. “op codes”, “machine code”, etc.) and which produces corresponding output signals that are applied to operate a machine. A processor may, for example, be 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) or any combination thereof. A processor may further be a multi-core processor having two or more independent processors (sometimes referred to as “cores”) that may execute instructions contemporaneously.
“TIMESTAMP” in this context refers to a sequence of characters or encoded information identifying when a certain event occurred, for example giving date and time of day, sometimes accurate to a small fraction of a second.
This application is a continuation of and claims the benefit of priority of U.S. patent application Ser. No. 15/492,089, filed on Apr. 20, 2017, which is hereby incorporated by reference herein in its entirety.
| 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 | 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 et al. | 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 et al. | 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 | Spriestersbach et al. | Mar 2006 | B2 |
| 7027124 | Foote et al. | Apr 2006 | B2 |
| 7072963 | Anderson et al. | Jul 2006 | B2 |
| 7085571 | Kalhan 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 et al. | Jul 2007 | B1 |
| 7269426 | Kekkonen et al. | 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 |
| 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 |
| 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 |
| 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 | Beilegarda 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 |
| 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 |
| 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 |
| 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 et al. | Dec 2017 | B2 |
| 9854219 | Sehn | Dec 2017 | B2 |
| 9922431 | Gray | Mar 2018 | B2 |
| 9961520 | Brooks et al. | May 2018 | B2 |
| 9984499 | Jurgenson et al. | May 2018 | B1 |
| 10074381 | Cowburn | Sep 2018 | B1 |
| 10102680 | Jurgenson et al. | Oct 2018 | B2 |
| 10366543 | Jurgenson et al. | Jul 2019 | B1 |
| 10387730 | Cowburn | Aug 2019 | B1 |
| 10497158 | Jain | Dec 2019 | B2 |
| 10733802 | Jurgenson et al. | Aug 2020 | 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 | 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 | Wugofski | 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 | 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 | 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 | Crowley 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 et al. | 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 |
| 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 et al. | 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 |
| 20080288338 | Wiseman et al. | Nov 2008 | A1 |
| 20080306826 | Kramer | 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 | 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 et al. | Aug 2009 | A1 |
| 20090232354 | Camp, Jr. | 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 | Polachek | 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 |
| 20100162149 | Sheleheda | 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 | Nov 2010 | A1 |
| 20100306669 | Della Pasqua | 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 |
| 20110096093 | Oi et al. | Apr 2011 | A1 |
| 20110099507 | Nesladek et al. | 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 |
| 20110279453 | Murphy | 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 | 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 |
| 20120001651 | Lalancette et al. | Jun 2012 | A1 |
| 20120143760 | Abulafia et al. | Jun 2012 | A1 |
| 20120146991 | Bala | Jun 2012 | A1 |
| 20120150978 | Monaco | 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 | Bianchflower 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 |
| 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 |
| 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 |
| 20130002649 | Wu 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 | 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 |
| 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 |
| 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 |
| 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 | Mckenzle | 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 |
| 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 | Jan 2014 | A1 |
| 20140032682 | Prado et al. | Jan 2014 | A1 |
| 20140000432 | 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 |
| 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 |
| 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 |
| 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 | Leyden | Apr 2015 | A1 |
| 20150096042 | Mizrachi | Apr 2015 | A1 |
| 20150116529 | Wu et al. | Apr 2015 | A1 |
| 20150169827 | Laborde | Jun 2015 | A1 |
| 20150172534 | Miyakawaa et al. | Jun 2015 | A1 |
| 20150178257 | Jones | 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 |
| 20150261917 | Smith | Sep 2015 | A1 |
| 20150312184 | Langholz et al. | Oct 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 |
| 20160085773 | Chang | Mar 2016 | A1 |
| 20160085863 | Allen et al. | Mar 2016 | A1 |
| 20160086670 | Gross et al. | Mar 2016 | A1 |
| 20160099901 | Allen et al. | Apr 2016 | A1 |
| 20160180887 | Sehn | Jun 2016 | A1 |
| 20160182422 | Sehn et al. | Jun 2016 | A1 |
| 20160182875 | Sehn | Jun 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 |
| 20170124713 | Jurgensen et al. | May 2017 | A1 |
| 20170161382 | Ouimet et al. | Jun 2017 | A1 |
| 20170161558 | Ludwigsen | Jun 2017 | A1 |
| 20170237789 | Harner et al. | Aug 2017 | A1 |
| 20170243371 | Jurgenson et al. | Aug 2017 | A1 |
| 20170263029 | Yan | Sep 2017 | A1 |
| 20170287006 | Azmoodeh et al. | Oct 2017 | A1 |
| 20170295250 | Samaranayake et al. | Oct 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 |
| 20190073832 | Kim | Mar 2019 | A1 |
| 20190156534 | Chen et al. | May 2019 | A1 |
| 20190295326 | Jurgenson et al. | Sep 2019 | A1 |
| 20190347323 | Riesa | Nov 2019 | A1 |
| 20200250889 | Li | Aug 2020 | A1 |
| 20200327738 | Jurgenson et al. | Oct 2020 | A1 |
| Number | Date | Country |
|---|---|---|
| 2887596 | Jul 2015 | CA |
| 2051480 | Apr 2009 | EP |
| 2151797 | Feb 2010 | EP |
| 2399928 | Sep 2004 | GB |
| 19990073076 | Oct 1999 | KR |
| 20010078417 | Aug 2001 | KR |
| 20110071210 | Jun 2011 | KR |
| 20130137063 | Dec 2013 | KR |
| 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-2013008238 | Jan 2013 | WO |
| WO-2013008251 | Jan 2013 | WO |
| WO-2013045753 | Apr 2013 | WO |
| WO-2014006129 | 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-2017176739 | Oct 2017 | WO |
| WO-2017176992 | Oct 2017 | WO |
| WO-2018005644 | Jan 2018 | WO |
| WO-2020160261 | Aug 2020 | WO |
| Entry |
|---|
| Traffic Sign Detection and Classification using Colour Feature and Neural Network, Md. Abdul Alim Sheikh et al., IEEE, 978-1-5090-2638-8, 2016, pp. 307-311 (Year: 2016). |
| Trademark detection using SIFT features matching, Ashwini D. Narhare et al., IEEE, 978-1-4799-6892-3, 2015, pp. 684-688 (Year: 2015). |
| Autonomous UAV Forced Graffiti Detection and Removal System Based on Machine Learning, Prakhar Nahar et al., IEEE, 978-1-5386-0435-9, 2017, pp. 1-8 (Year: 2017). |
| “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. 14/954,090, 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. 15/492,089, 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 dataed 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 mailed Sep. 19, 2017”, 2 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, 208”, 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. 16/135,849, Preliminary Amendment filed Oct. 15, 2018”, 10 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. |
| “BlogStomp”, StompSoftware, [Online] Retrieved from the internet: <URL: http://stompsoftware.com/blogstomp>, (accessed May 24, 2017), 12 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 (OS/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. |
| “InstaPlace Photo App Tell The Whole Story”, [Online] Retrieved from the internet: <URL: https://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. |
| “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. |
| “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-Reality-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), 88 pgs.; 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-Return>, (Nov. 15, 2011), 5 pgs. |
| Carthy, Roi, “Dear All Photo Apps: Mobli 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-android-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. |
| Melanson, Mike, “This text message will self destruct in 60 seconds”, [Online] Retrieved from the internet: <URL: http://readwrite.com/2011/02/11/this_text_message_will_self_destruct_in_60_seconds>, (Feb. 18, 2015), 4 pgs. |
| 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. |
| 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-server>, (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/StealthTextShouldYauChoosetoAcceptIt>, (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. |
| “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. 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. 15/706,074, 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. 15/971,566, 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, Response filed Jan. 31, 2019 to Final Office Action dated Oct. 31, 2018”, 12 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. 16/136,849, Corrected Notice of Allowability dated Apr. 25, 2019”, 4 pgs. |
| “U.S. Appl. No. 16/438,226, Non Final Office Action dated Jul. 10, 2019”, 6 pgs. |
| “Deltatre and Vizrt expanding partnership for Magma Pro Football solution”, Vizrt (Online), 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, Response filed Dec. 7, 2018 to Communication Pursuant to Rules 161(1) and 162 EPC dated Jun. 7, 2018”, w/ English Claims, 114 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/US2016/959503, Written Opinion dated Jan. 23, 2017”, 5 pgs. |
| “Korean Application Serial No. 10-2017-7035785, Notice of Preliminary Rejection dated Dec. 28, 2018”, w/ English Translation, 10 pgs. |
| “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. |
| 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. |
| U.S. Appl. No. 16/913,503, filed Jun. 26, 2020, Image Based Tracking in Augmented Reality Systems. |
| “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. 16/438,226, Final Office Action dated Jan. 3, 2020”, 10 pgs. |
| “U.S. Appl. No. 16/265,382, Non Final Office Action dated Mar. 3, 2020”, 18 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, Notice of Allowance dated Mar. 26, 2020”, 8 pgs. |
| “U.S. Appl. No. 16/438,226, Corrected Notice of Allowability dated May 1, 2020”, 4 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, International Search Report dated Jul. 10, 2020”, 6 pgs. |
| “International Application Serial No. PCT/US2020/015868, Written Opinion dated Jul. 10, 2020”, 15 pgs. |
| “U.S. Appl. No. 16/265,382, Response filed Aug. 3, 2020 to Non Final Office Action dated Mar. 3, 2020”, 10 pgs. |
| Park, Jungsik, “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, “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, “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. |
| U.S. Appl. No. 14/954,090 U.S. Pat. No. 9,652,896, filed Nov. 30, 2015, Image Based Tracking in Augmented Reality Systems. |
| U.S. Appl. No. 15/591,887 U.S. Pat. No. 9,836,890, filed May 10, 2017, Image Based Tracking in Augmented Reality Systems. |
| U.S. Appl. No. 15/830,965 U.S. Pat. No. 10,102,680, filed Dec. 4, 2017, Image Based Tracking in Augmented Reality Systems. |
| U.S. Appl. No. 16/136,849 U.S. Pat. No. 10,366,543, filed Sep. 20, 2018, Image Based Tracking in Augmented Reality Systems. |
| U.S. Appl. No. 16/438,226, filed Jun. 11, 2019, Image Based Tracking in Augmented Reality Systems. |
| U.S. Appl. No. 15/492,089 U.S. Pat. No. 10,387,730, filed Apr. 20, 2017, Augmented Reality Typography Personalization System. |
| U.S. Appl. No. 16/265,382, filed Feb. 1, 2019, Augmented Reality System. |
| “U.S. Appl. No. 16/265,382, Final Office Action dated Oct. 13, 2020”, 21 pgs. |
| “U.S. Appl. No. 16/265,382, Response filed Feb. 12, 2021 to Final Office Action dated Oct. 13, 2020”, 11 pgs. |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 15492089 | Apr 2017 | US |
| Child | 16433793 | US |
