Abstract: Techniques for measuring cloud-based input latency are described herein. In accordance with various embodiments, a server including one or more processors and a non-transitory memory receives from a client an input event corresponding to a request for a TV user interface (UI). The server adds a tag to each of a set of screens corresponding to the TV UI and records event data corresponding to the input event prior to rendering the set of screens into a set of rendered frames. The server additionally decodes the tag in the set of rendered frames to generate metadata that associate the event data with the set of rendered frames prior to encoding the set of rendered frames into a set of encoded frames. The server also transmits to the client the set of encoded frames and the metadata.

Abstract: A method includes transmitting a first preauthored video frame of a plurality of preauthored video frames to a client device. The first preauthored video frame is associated with a preauthored media object. The method includes providing a request for a composited video frame to an interactive source device. The request includes a temporal characteristic associated with the first preauthored video frame. The method includes, in response to providing the request, obtaining, from the interactive source device, the composited video frame including customizable video content and preauthored video content. The preauthored video content is associated with a portion of the preauthored media object based on the temporal characteristic.

Abstract: Techniques for targeting media content items for weakly connected devices are described. In some embodiments, a model building method in preparation for approximated personalization is performed at a server. The server uses data from fully connected devices to build a full model, which classifies profiles into clusters and tags targeted content with content rankings. The server also builds device models that approximate the full model. The server then sends the device models to user devices for targeted content selection. In some embodiments, a content selection method for approximated personalization is performed at a user device. The user device receives parameters of a device model trained by a server. The user device then executes the device model using local user data to assign a profile to a cluster and selects targeted content for the profile based on the cluster assignment and the rankings of the targeted content.

Abstract: A method includes determining a first transmission rate for transmitting an entirety of a segment of a video stream to a client device. The segment includes a set of frames. In some implementations, the method includes, after transmitting a first subset of the set of frames at the first transmission rate, detecting that a network connectivity of the client device has reduced below a connectivity threshold associated with the first transmission rate. In some implementations, the method includes transmitting an entirety of the segment at a second transmission rate that is less than the first transmission rate. In some implementations, the method includes triggering the client device to present a second subset of the set of frames that corresponds to a temporal position in the video stream after the first subset of the set of frames while foregoing re-presentation of the first subset of the set of frames.

Abstract: In some implementations, a device includes one or more processors and a non-transitory memory. In some implementations, a method includes obtaining a request to perform a user interface operation at a client device while the client device is playing a media content item in a buffered content presentation mode. In some implementations, the method includes identifying a first image that represents a current playback position of the media content item at the client device. In some implementations, the method includes identifying a second image that represents a user interface element associated with the user interface operation. In some implementations, the method includes generating a first video frame that corresponds to the user interface operation by blending the first image with the second image. In some implementations, the method includes triggering the client device to present the first video frame in a real-time content presentation mode.

Abstract: Techniques for a trusted system for secure content distribution and trusted recording of content consumption are described. In some embodiments, the trusted system transcodes and transcrypts a media content item using a key obtained from a content provider and one or more keys based on an entitlement from a service provider to generate an encrypted media content item. The trusted system further receives a request to provide the media content item to a client device. The trusted system also obtains a signed audit token recording the request upon an authorization by the service provider based on the entitlement and a confirmation by the content provider, where the signed audit token is signed by the content provider and the service provider. The trusted system additionally provides the one or more keys for decrypting the encrypted media content item and reports the signed audit token.

Abstract: Techniques for allocating bandwidth for low latency content and buffered content are described. In accordance with various embodiments, a bandwidth allocation method is performed at a device (e.g., a server) with one or more processors and a non-transitory memory. The server determines available bandwidth for delivering content to a client device in a stream, where the stream includes low latency content and buffered content. The server further identifies characteristics of the low latency content. The server then allocates a first portion of the available bandwidth to the low latency content and a second portion of the available bandwidth to the buffered content based on the characteristics of the low latency content.

Abstract: Techniques for providing multimedia content in a virtual set top system are described. In some embodiments, a stream switchover method for UI rendering is performed at a device (e.g., a server) with one or more processors and a non-transitory memory. The server distributes a first stream that includes a plurality of frames. The server receives a request for a user interface (UI) from a client. In response to receiving the request, the server generates a second stream by locating an encoder to encode the plurality of frames into the second stream based on the first stream, instructing the encoder to accelerate encoding of the plurality of frames and facilitating blending of the UI into the second stream with the plurality of frames. The server then switches the client from the first stream to the second stream.

Abstract: A method includes determining a first transmission rate for transmitting an entirety of a segment of a video stream to a client device. The segment includes a set of frames. In some implementations, the method includes, after transmitting a first subset of the set of frames at the first transmission rate, detecting that a network connectivity of the client device has reduced below a connectivity threshold associated with the first transmission rate. In some implementations, the method includes transmitting an entirety of the segment at a second transmission rate that is less than the first transmission rate. In some implementations, the method includes triggering the client device to present a second subset of the set of frames that corresponds to a temporal position in the video stream after the first subset of the set of frames while foregoing re-presentation of the first subset of the set of frames.

Abstract: Techniques for allocating bandwidth for low latency content and buffered content are described. In accordance with various embodiments, a bandwidth allocation method is performed at a device (e.g., a server) with one or more processors and a non-transitory memory. The server determines available bandwidth for delivering content to a client device in a stream, where the stream includes low latency content and buffered content. The server further identifies characteristics of the low latency content. The server then allocates a first portion of the available bandwidth to the low latency content and a second portion of the available bandwidth to the buffered content based on the characteristics of the low latency content.

Abstract: Various implementations disclosed herein include devices, systems, and methods for reducing a decode delay at a client device. In some implementations, a device includes one or more processors and a non-transitory memory. In some implementations, a method includes determining that a client device is being switched from a real-time content presentation mode in which the client device presents real-time content to a buffered content presentation mode in which the client device presents buffered content. In some implementations, the method includes transmitting, to the client device, video frames corresponding to the buffered content at a first transmission rate. In some implementations, the method includes changing the first transmission rate to a second transmission rate based on an indication that a number of bits stored in a buffer of the client device satisfies a decode threshold.

Abstract: In some implementations, a device includes one or more processors and a non-transitory memory. In some implementations, a method includes obtaining a request for a sequence of video frames that corresponds to a user interface operation being performed at a client device. In some implementations, the sequence of video frames is to be presented at the client device at a first frame rate. In some implementations, the method includes determining an availability of computing resources associated with providing the sequence of video frames to the client device. In some implementations, the method includes generating, based on the availability of computing resources, the sequence of video frames at a second frame rate that is greater than the first frame rate. In some implementations, the method includes triggering the client device to present the sequence of video frames at the first frame rate.

Abstract: In some implementations, a device includes one or more processors and a non-transitory memory. In some implementations, a method includes determining that a video frame to be presented at a client device includes a portion that corresponds to a particular playback position within a video content item. In some implementations, the method includes obtaining audio data that corresponds to the particular playback position within the video content item. In some implementations, the method includes transmitting the audio data to the client device separate from the video frame.

Abstract: A method includes transmitting a first preauthored video frame of a plurality of preauthored video frames to a client device. The first preauthored video frame is associated with a preauthored media object. The method includes providing a request for a composited video frame to an interactive source device. The request includes a temporal characteristic associated with the first preauthored video frame. The method includes, in response to providing the request, obtaining, from the interactive source device, the composited video frame including customizable video content and preauthored video content. The preauthored video content is associated with a portion of the preauthored media object based on the temporal characteristic.

Abstract: In some implementations, a device includes one or more processors and a non-transitory memory. In some implementations, a method includes obtaining a request to perform a user interface operation at a client device while the client device is playing a media content item in a buffered content presentation mode. In some implementations, the method includes identifying a first image that represents a current playback position of the media content item at the client device. In some implementations, the method includes identifying a second image that represents a user interface element associated with the user interface operation. In some implementations, the method includes generating a first video frame that corresponds to the user interface operation by blending the first image with the second image. In some implementations, the method includes triggering the client device to present the first video frame in a real-time content presentation mode.

Abstract: In some implementations, a device includes one or more processors and a non-transitory memory. In some implementations, a method includes determining that a video frame to be presented at a client device includes a portion that corresponds to a particular playback position within a video content item. In some implementations, the method includes obtaining audio data that corresponds to the particular playback position within the video content item. In some implementations, the method includes transmitting the audio data to the client device separate from the video frame.

Abstract: Techniques for targeting media content items for weakly connected devices are described. In some embodiments, a model building method in preparation for approximated personalization is performed at a server. The server uses data from fully connected devices to build a full model, which classifies profiles into clusters and tags targeted content with content rankings. The server also builds device models that approximate the full model. The server then sends the device models to user devices for targeted content selection. In some embodiments, a content selection method for approximated personalization is performed at a user device. The user device receives parameters of a device model trained by a server. The user device then executes the device model using local user data to assign a profile to a cluster and selects targeted content for the profile based on the cluster assignment and the rankings of the targeted content.

Abstract: Techniques for providing multimedia content in a virtual set top system are described. In some embodiments, a stream switchover method for UI rendering is performed at a device (e.g., a server) with one or more processors and a non-transitory memory. The server distributes a first stream that includes a plurality of frames. The server receives a request for a user interface (UI) from a client. In response to receiving the request, the server generates a second stream by locating an encoder to encode the plurality of frames into the second stream based on the first stream, instructing the encoder to accelerate encoding of the plurality of frames and facilitating blending of the UI into the second stream with the plurality of frames. The server then switches the client from the first stream to the second stream.

Abstract: Techniques for targeting media content items for weakly connected devices are described. In some embodiments, a model building method in preparation for approximated personalization is performed at a server. The server uses data from fully connected devices to build a full model, which classifies profiles into clusters and tags targeted content with content rankings. The server also builds device models that approximate the full model. The server then sends the device models to user devices for targeted content selection. In some embodiments, a content selection method for approximated personalization is performed at a user device. The user device receives parameters of a device model trained by a server. The user device then executes the device model using local user data to assign a profile to a cluster and selects targeted content for the profile based on the cluster assignment and the rankings of the targeted content.

Abstract: Techniques for targeting media content items for weakly connected devices are described. In some embodiments, a model building method in preparation for approximated personalization is performed at a server. The server uses data from fully connected devices to build a full model, which classifies profiles into clusters and tags targeted content with content rankings. The server also builds device models that approximate the full model. The server then sends the device models to user devices for targeted content selection. In some embodiments, a content selection method for approximated personalization is performed at a user device. The user device receives parameters of a device model trained by a server. The user device then executes the device model using local user data to assign a profile to a cluster and selects targeted content for the profile based on the cluster assignment and the rankings of the targeted content.