New systems and methods allow for transmission of multiple types of content protocols over a unidirectional content delivery network, such as a television broadcast. Hardware and/or software used at the network transmission location (such as a television broadcast station) and hardware and/or software located at an endpoint (such as a home television, car infotainment system, or first responder location) allow for a native ATSC 1.0 signal to have embedded within it additional content that is not encoded as ATSC 1.0 content. The non-ATSC 1.0 content can be detected and segregated from ATSC 1.0 content so that the endpoint devices (such as a television receiver) will not attempt to render the non-ATSC 1.0 content (such as, e.g., ATSC 3.0 content or application specific content) as normal ATSC 1.0 programming. Instead, the non-ATSC 1.0 content will be separately decoded, assembled, and processed to allow for multiple types of content to be used and displayed by the endpoint, even though the broadcast signal was transmitted only as an ATSC 1.0 signal.

Method, apparatus and computer readable media for receiving a multiprogram program transport service that includes one or more compressed video services and one or more 3D-2D conversion options, generating an uncompressed video signal by performing a decoding portion of a transcoding operation for one of the one or more of the video services, determining from the 3D-2D conversion option whether a 3D-2D conversion is to be performed, performing a scale conversion on the uncompressed video according to a specified type of 3D-2D conversion, generating a compressed video service by performing an encoding portion of a transcoding operation on the uncompressed video that has been scale converted, and generating a second multiprogram program transport service that includes the compressed video signal that has been 3D-2D converted.

An apparatus including an interface and a processor. The interface may be configured to receive pixel data generated by a capture device. The processor may be configured to generate video frames in response to the pixel data, perform computer vision operations on the video frames to detect objects, perform a classification of the objects detected based on characteristics of the objects, determine whether the classification of the objects corresponds to a user-defined event and generate encoded video frames from the video frames. The encoded video frames may be communicated to a cloud storage service. The encoded video frames may comprise a first sample of the video frames selected at a first rate when the user-defined event is not detected and a second sample of the video frames selected at a second rate while the user-defined event is detected. The second rate may be greater than the first rate.

Methods and systems for storage and playback of broadcast media received via a local digital video recording (DVR) system. The system includes the DVR system configured to receive the broadcast media and upload the broadcast media to a storage server over a network. The DVR system divides the broadcast media content into blocks and assigns a unique block ID to each block based on the block data. Prior to uploading each block to the storage server, the unique block ID is sent to the storage server, which only uploads and stored the block if a duplicate block has not already been stored on the storage device, minimizing network demand. A transcoding server coupled to the storage server transcodes the broadcast media content for streaming over the network.

A system and method for remotely transcoding content includes a cloud location storing content corresponding to content titles, generating a playlist corresponding to content titles subscribed to by a user of a user device stored therein, and communicating the playlist to the user device. A user device is in communication with the cloud location through a network. The user device generates a selection signal for selecting a first content title from the playlist to form a selection. The user device negotiates optimal settings by intercommunicating between the user device and the cloud location in response to forming the selection. The user device communicates the selection to the cloud location. The cloud location has a transcoder device transcoding content corresponding to the selection to form transcoded content in response to the optimal settings. The cloud location communicates the transcoded content to the user device.

A method, a system, a terminal and a server for switching from a video live stream to video-on-demand data are provided. The method includes: sending, by a terminal, a video acquisition request for a target video to a server; acquiring, by the server, video data of the target video from a live stream of the target video in response to the video acquisition request, and storing the acquired video data of the target video; sending, by the terminal, a video editing request for the target video to the server; performing, by the server, non-linear editing on the video data of the target video in response to the video editing request; and storing, by the server, the edited video data as video-on-demand data of the target video.

The present disclosure provides a method and system for real time, dynamic, adaptive and non-sequential assembling of one or more mapped fragments of one or more tagged videos. The method includes a step of receiving a set of preference data from pre-defined selection criteria and set of user authentication data. The method includes another step of fetching the one or more tagged videos from the digitally processed repository of videos. The method includes yet another step of fragmenting each tagged video of the one or more tagged videos into the one or more tagged fragments and clustering one or more logical sets of mapped fragments into one or more logical clusters of mapped fragments. The method includes yet another step of assembling at least one of the one or more logical clusters of mapped fragments in a pre-defined order of preference to obtain an assembled video.

A method includes performing a conversion between a video including a video picture including one or more tiles and a bitstream of the video. The video picture refers to a picture parameter set, and the picture parameter set conforms to a format rule specifying that the picture parameter set includes a list of column widths for N tile columns, where N is an integer. An (N−1)-th tile column exists in the video picture and the (N−1)-th tile column has a width that is equal to an (N−1)-th entry in a list of explicitly included tile column widths plus one number of coding tree blocks.

An online system receives video data items from users and encodes the video data items using various codecs. To account for different computational resources used for encoding using different codecs, the online system ranks combinations of video data items by ratios of encoding video data items with different codecs to computational costs of encoding different video data items with different codecs. The benefit of encoding a video data item with a codec is based on a compression efficiency of the codec and a predicted aggregate amount of the video data item displayed to various users of the online system. Encoding video data items with codecs based on the determined ratios allows the online system to optimize a duration of video data having at least a threshold video quality to users.

The Cloud-based Video Streaming Service (CVSS) architecture is disclosed to transcode video streams in an on-demand manner. The architecture provides a platform for streaming service providers to utilize cloud resources in a cost-efficient manner and with respect to the Quality of Service (QoS) demands of video streams. In particular, the architecture includes a QoS-aware scheduling method to efficiently map video streams to cloud resources, and a cost-aware dynamic (i.e., elastic) resource provisioning policy that adapts the resource acquisition with respect to the video streaming QoS demands. Simulation results based on realistic cloud traces and with various workload conditions, demonstrate that the CVSS architecture can satisfy video streaming QoS demands and reduces the incurred cost of stream providers up to 70%.