Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving a first input associated with a bookmark and, in response to receiving the first input, obtaining context data for deriving annotations for the bookmark. An annotation engine of a system obtains multiple annotations that are derived using information included in the context data and a transcription of the first input associated with the bookmark. The annotation engine generates an importance value for each annotation. The importance value characterizes a relationship between each annotation and at least one of: the information included in the context data; or the transcription of the first input. The annotation engine generates a set of annotations for retrieving the bookmark. Each annotation in the set of annotations is generated from the obtained multiple annotations and each annotation has an importance value that exceeds a threshold value.

Abstract: Multiple snapshots of a scene are captured within an executing application (e.g., a video game). When each snapshot is captured, associated color values per pixel and a distance or depth value z per pixel are stored. The depth information from the snapshots is accessed, and a point cloud representing the depth information is constructed. A mesh structure is constructed from the point cloud. The light field(s) on the surface(s) of the mesh structure are calculated. A surface light field is represented as a texture. A renderer uses the surface light field with geometry information to reproduce the scene captured in the snapshots. The reproduced scene can be manipulated and viewed from different perspectives.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving a first input associated with a bookmark and, in response to receiving the first input, obtaining context data for deriving annotations for the bookmark. An annotation engine of a system obtains multiple annotations that are derived using information included in the context data and a transcription of the first input associated with the bookmark. The annotation engine generates an importance value for each annotation. The importance value characterizes a relationship between each annotation and at least one of: the information included in the context data; or the transcription of the first input. The annotation engine generates a set of annotations for retrieving the bookmark. Each annotation in the set of annotations is generated from the obtained multiple annotations and each annotation has an importance value that exceeds a threshold value.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving a first input associated with a bookmark and, in response to receiving the first input, obtaining context data for deriving annotations for the bookmark. An annotation engine of a system obtains multiple annotations that are derived using information included in the context data and a transcription of the first input associated with the bookmark The annotation engine generates an importance value for each annotation. The importance value characterizes a relationship between each annotation and at least one of: the information included in the context data; or the transcription of the first input. The annotation engine generates a set of annotations for retrieving the bookmark. Each annotation in the set of annotations is generated from the obtained multiple annotations and each annotation has an importance value that exceeds a threshold value.

Abstract: Multiple snapshots of a scene are captured within an executing application (e.g., a video game). When each snapshot is captured, associated color values per pixel and a distance or depth value z per pixel are stored. The depth information from the snapshots is accessed, and a point cloud representing the depth information is constructed. A mesh structure is constructed from the point cloud. The light field(s) on the surface(s) of the mesh structure are calculated. A surface light field is represented as a texture. A renderer uses the surface light field with geometry information to reproduce the scene captured in the snapshots. The reproduced scene can be manipulated and viewed from different perspectives.

Abstract: Multiple snapshots of a scene are captured within an executing application (e.g., a video game). When each snapshot is captured, associated color values per pixel and a distance or depth value z per pixel are stored. The depth information from the snapshots is accessed, and a point cloud representing the depth information is constructed. A mesh structure is constructed from the point cloud. The light field(s) on the surface(s) of the mesh structure are calculated. A surface light field is represented as a texture. A renderer uses the surface light field with geometry information to reproduce the scene captured in the snapshots. The reproduced scene can be manipulated and viewed from different perspectives.

Abstract: Multiple snapshots of a scene are captured within an executing application (e.g., a video game). When each snapshot is captured, associated color values per pixel and a distance or depth value z per pixel are stored. The depth information from the snapshots is accessed, and a point cloud representing the depth information is constructed. A mesh structure is constructed from the point cloud. The light field(s) on the surface(s) of the mesh structure are calculated. A surface light field is represented as a texture. A renderer uses the surface light field with geometry information to reproduce the scene captured in the snapshots. The reproduced scene can be manipulated and viewed from different perspectives.

Abstract: Methods, apparatuses, and/or systems are providing for enabling a time-shifted, on-demand social network for watching, creating, and/or sharing time-shifted annotation datasets (e.g., commentary tracks) synced to any on-demand programming, and more particularly to providing rewards to users when they create annotations (e.g., comments), when other users interact with their annotations, when transactions are enabled via their annotations, or for other reasons.

Abstract: The disclosed embodiments relate to a method, apparatus, and computer-readable medium for providing an interaction package to a user based at least in part on metadata associated with content. An exemplary method comprises processing metadata associated with content, determining information corresponding to an interaction package for a user based at least in part on the metadata, wherein at least a portion of the interaction package is associated with the content, and transmitting the information corresponding to the interaction package to at least one of one or more user computing devices. The disclosed embodiments further relates to a method, apparatus, and computer-readable medium for presenting at least a portion of an interaction package to a user based at least in part on metadata associated with content.

Abstract: Methods, apparatuses, and/or systems are providing for enabling a time-shifted, on-demand social network for watching, creating, and/or sharing time-shifted annotation datasets (e.g., commentary tracks) synced to any on-demand programming, and more particularly to providing rewards to users when they create annotations (e.g., comments), when other users interact with their annotations, when transactions are enabled via their annotations, or for other reasons.

Abstract: Methods, apparatuses, and/or systems are provided for enabling a time-shifted, on-demand social network for watching, creating, and/or sharing time-shifted annotation datasets (e.g., commentary tracks) synced to any on-demand programming, and for enabling sharing of access to portions of a content item with users across a plurality of content delivery services.

Abstract: Methods, apparatuses, and/or systems are provided for enabling a time-shifted, on-demand social network for watching, creating, and/or sharing time-shifted annotation datasets (e.g., commentary tracks) synced to any on-demand programming, and more particularly for creating and maintaining a database of annotations corresponding to portions of a content item.

Abstract: Methods, apparatuses, and/or systems are provided for enabling a time-shifted, on-demand social network for watching, creating, and/or sharing time-shifted annotation datasets (e.g., commentary tracks) synced to any on-demand programming, and for managing reactions to annotations (e.g., comments).

Abstract: Methods, apparatuses, and/or systems are provided for enabling a time-shifted, on-demand social network for watching, creating, and/or sharing time-shifted annotation datasets (e.g., commentary tracks) synced to any on-demand programming, and for presenting content items, annotations (e.g., comments) associated with the content items, or related items.

Abstract: Methods, apparatuses, and/or systems are provided for enabling a time-shifted, on-demand social network for watching, creating, and/or sharing time-shifted annotation datasets (e.g., commentary tracks) synced to any on-demand programming, and more particularly to providing (e.g., displaying) annotations (e.g., comments) received during presentations of a content item.