# US 10,769,199 B2 · Systems and methods for processing media content that depict objects > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,769,199 B2 - Document ID: US10769199B2 - Status: Granted - Kind: B2 - Application number: 16/356,383 - Filed: 2019-03-18 - Published: 2020-01-02 - Granted: 2020-09-08 - Earliest claimed: 2016-08-31 - Assignees: Facebook, Inc. - Applicants: Facebook, Inc. - Inventors: William M. Ruben; Zachary W. Gomez - Web page: https://patentgrep.com/patent/US10769199B2 ## CPC - G06V 10/762: using clustering, e.g. of similar faces in social networks - G06F 16/5838: {using colour} - G06F 16/5854: {using shape and object relationship} - G06F 18/24765: {Rule-based classification} - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract Access to a set of media content items is acquirable. Identified processors can perform, in parallel, object detection for the set. In some cases, information about a current system state, a user, and/or object popularity metrics is acquirable for selecting a subset of object models. Object recognition is performable, based on the subset, for the set of media content items. In some instances, a camera view can be provided. Object recognition is performable for representations of the view. An object depicted in the representations is identifiable. An interface portion is presentable to provide a label for the object. In some cases, object recognition is performable for the set of media content items to identify an object depicted in a content item. A label is associable with the content item. A search through the set of media content items can identify, based on the label, a subset that depicts the object. ## Claims ### Claim 1 A computer-implemented method comprising: selecting, by a computing system, a set of object models, wherein each object model in the set of object models represents an object that satisfies a threshold likelihood confidence value of being associated with a location associated with a device; and providing, by the computing system, the set of object models, wherein object recognition can be performed by the device to identify the object based on the set of object models. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein each object model in the set of object models is trained to identify a respective object that each object model represents. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, wherein each object model in the set of object models enables the device to perform object recognition locally on the device. ### Claim 4 (depends on 1) The computer-implemented method of claim 1, wherein the device is associated with a user and selecting the set of object models is based at least in part on one or more social connections associated with the user and a respective frequency with which each object model is utilized by the one or more social connections. ### Claim 5 (depends on 1) The computer-implemented method of claim 1, wherein the device is associated with a user and selecting the set of object models is based at least in part on one or more interactions between the user and a social networking system. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, wherein the device has acquired a threshold quantity of media content items that depict a particular object and at least one object model in the set of object models represents the particular object. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein at least one object model in the set of object models represents a popular object associated with an object popularity value that satisfies an object popularity threshold. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, wherein at least one object model in the set of object models satisfies a threshold confidence likelihood value of being associated with a time associated with the device. ### Claim 9 (depends on 1) The computer-implemented method of claim 1, wherein the set of object models enables the device to search media content items on the device based on at least one of topics, object names, or object categories. ### Claim 10 (depends on 1) The computer-implemented method of claim 1, wherein the object recognition performed by the device is with respect to one or more images acquired by the device. ### Claim 11 A system comprising: at least one processor; and a memory storing instructions that, when executed by the at least one processor, cause the system to perform a method comprising: selecting a set of object models, wherein each object model in the set of object models represents an object that satisfies a threshold likelihood confidence value of being associated with a location associated with a device; and providing the set of object models, wherein object recognition can be performed by the device to identify the object based on the set of object models. ### Claim 12 (depends on 11) The system of claim 11, wherein each object model in the set of object models is trained to identify a respective object that each object model represents. ### Claim 13 (depends on 11) The system of claim 11, wherein each object model in the set of object models enables the device to perform object recognition locally on the device. ### Claim 14 (depends on 11) The system of claim 11, wherein the device is associated with a user and selecting the set of object models is based at least in part on one or more social connections associated with the user and a respective frequency with which each object model is utilized by the one or more social connections. ### Claim 15 (depends on 11) The system of claim 11, wherein the device is associated with a user and selecting the set of object models is based at least in part on one or more interactions between the user and a social networking system. ### Claim 16 A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform a method comprising: selecting a set of object models, wherein each object model in the set of object models represents an object that satisfies a threshold likelihood confidence value of being associated with a location associated with a device; and providing the set of object models, wherein object recognition can be performed by the device to identify the object based on the set of object models. ### Claim 17 (depends on 16) The non-transitory computer-readable storage medium of claim 16, wherein each object model in the set of object models is trained to identify a respective object that each object model represents. ### Claim 18 (depends on 16) The non-transitory computer-readable storage medium of claim 16, wherein each object model in the set of object models enables the device to perform object recognition locally on the device. ### Claim 19 (depends on 16) The non-transitory computer-readable storage medium of claim 16, wherein the device is associated with a user and selecting the set of object models is based at least in part on one or more social connections associated with the user and a respective frequency with which each object model is utilized by the one or more social connections. ### Claim 20 (depends on 16) The non-transitory computer-readable storage medium of claim 16, wherein the device is associated with a user and selecting the set of object models is based at least in part on one or more interactions between the user and a social networking system.