A terminal for receiving streaming data may receive information of a plurality of different quality versions of an image content; request, based on the information, a server for a version of the image content from among the plurality of different quality versions of the image content; when the requested version of the image content and artificial intelligence (AI) data corresponding to the requested version of the image content are received, determines whether to perform AI upscaling on the received version of the image content, based on the AI data; and based on a result of the determining whether to perform AI upscaling, performs AI upscaling on the received version of the image content through a upscaling deep neural network (DNN) that is trained jointly with a downscaling DNN of the server.

A terminal for receiving streaming data may receive information of a plurality of different quality versions of an image content; request, based on the information, a server for a version of the image content from among the plurality of different quality versions of the image content; when the requested version of the image content and artificial intelligence (AI) data corresponding to the requested version of the image content are received, determines whether to perform AI upscaling on the received version of the image content, based on the AI data; and based on a result of the determining whether to perform AI upscaling, performs AI upscaling on the received version of the image content through a upscaling deep neural network (DNN) that is trained jointly with a downscaling DNN of the server.

A processing method for processing videos from multiple channels includes: assigning first multimedia data to a hardware decoder circuit to generate first decoded data; assigning second multimedia data to a software decoder circuit to generate second decoded data; and duplicating the first decoded data and the second decode data to a video buffer according to a predetermined arrangement and an encoding format to generate output data, for being displayed by a screen. The predetermined arrangement indicates an arrangement of display regions corresponding to the first multimedia data and the second multimedia data on the screen.

In order for a terminal to play a video, a first video file is obtained. The first video file is sliced to generate a plurality of first slice files. A play index is generated to include entries respectively corresponding to the first slice files. An entry corresponding to a second video file is inserted into the index between an entry corresponding to one first slice file and an entry corresponding to another first slice file in the play index. The first slice files are played in sequence according to the play index, and the second vide file is played after the one of the first slice files and before the other of the first slice files according to the play index.

The invention relates to a method for processing multimedia streams, in particular to verify access rights to a content of said multimedia stream, the multimedia stream being provided by a server device connected to a communication network, and downloadable by a client device via data formatted in a markup language, by using software for browsing and displaying data formatted in a markup language, cooperating with software for reading multimedia streams, the multimedia stream comprising at least one video stream able to be displayed in the form of pixels in a display zone (42, 44, 46, 48) of a display screen of the client device. The method includes determining a display zone (42), allocated by said browsing and display software to the software for reading multimedia streams in order to display a video stream extracted from said multimedia stream, and recording at least one digital image formed by values of the pixels to be displayed in the display zone (42) determined at a given time.

Novel tools and techniques to enable data to be tested on subscriber set-top boxes. Some solutions can connect a sever with a group of subscriber set-top boxes through a television distribution network. In some cases, a plurality of set-top boxes are selected, and at least one set-top box is determined to be inactive. In some cases, data are loaded and tested on the inactive set-top.

Providing a conditional access system (CAS) to a set-top box is described. An example method includes encapsulating a CAS application in a NCAS (Next CAS) container, and objects associated with the CAS application are executed in the NCAS container. Resources for the CAS application and other applications running on the set-top box are pre-allocated so that each application has a pre-fixed resource allocation upon startup of the set-top box. An execution of the CAS application is validated using a linked chain of trust.

Roughly described, a system and method for delivering video content to a user's client device in a video-on-demand (VOD) system, which includes providing a collection of video segments, the segments having a predefined default sequence; establishing a streaming video session according to a session-oriented protocol; transmitting toward the client device a script executable by the client device, the script operable to transmit navigational codes toward the head-end equipment in response to and indicating user selection among navigational choices; beginning transmission of the video segments in the collection toward the client device in accordance with the default sequence of segments; and in response to receipt of one of the navigational codes, and without tearing down the streaming video session, altering the transmission sequence to jump to the segment that the user selected.

The present disclosure relates to systems, methods, and non-transitory computer readable media for training and utilizing a generative machine learning model to select one or more treatments for a client device from a set of treatments based on digital characteristics corresponding to the client device. In particular, the disclosed systems can train and apply a variational autoencoder with a task embedding layer that generates estimated effects for treatment combinations. For example, the disclosed systems receive, as input, digital characteristics corresponding to the client device and various treatment combinations. The disclosed systems apply the trained generative machine learning model with the task embedding layer to the digital characteristics to generate effect estimations for the various treatment combinations. Based on the effect estimations for the treatment combinations, the disclosed systems select one or more treatments to provide to the client device.

Disclosed are various embodiments for facilitating uninterrupted playback of video streams using lower quality cached files. A video file corresponding to an entirety of a video content feature encoded at a first quality may be obtained from another client on a local network. A video stream corresponding to the video content feature encoded at a second quality higher than the first quality is then obtained. The video stream is rendered for playback on a display. In response to detecting an unavailability of the video stream at a particular time in the video content feature, the video file is rendered for playback on the display in place of the video stream and commences at the particular time in the video content feature. The video file may then be sent to yet another client on the local network.