Abstract: Bitrate-adaptive segmentation is performed for transcoding a video stream uploaded to an online video platform for hosting and later playback to platform users. The video stream is segmented into chunks based on prediction-based bit costs determined for frames of the video stream rather than based on scene changes detected within the video stream. The bitrate-adaptive segmentation includes determining inter-prediction bit costs and intra-prediction bit costs for frames of the video stream based on information indicated within a pass log based on a first pass encoding of the video stream, determining chunk boundaries for segmenting the video stream into a chunk based on the inter-prediction bit costs and the intra-prediction bit costs for the frames, and transcoding the chunk to produce a transcoded video stream.

Abstract: The invention relates to a piece of furniture made from a plurality of interconnectable planar elements (1, 2), in particular designed as a piece of children's furniture, such as a play house, wherein at least two of the adjacent planar elements (1, 2) are connectable by at least one plug connection, and wherein said plug connection is formed by a protrusion (3) which is formed on the end face of a first planar element (1) and which has an opening (4) extending crosswise to the flat side of the planar element (1), a recess (5) in a second planar element (2) into which the protrusion (3) of the first planar element (1) is insertable, and a securing element (6) which is interlockingly insertable into the opening (4) of the protrusion (3).

Abstract: The invention relates to a piece of furniture made from a plurality of interconnectable planar elements (1, 2), in particular designed as a piece of children's furniture, such as a play house, wherein at least two of the adjacent planar elements (1, 2) are connectable by at least one plug connection, and wherein said plug connection is formed by a protrusion (3) which is formed on the end face of a first planar element (1) and which has an opening (4) extending crosswise to the flat side of the planar element (1), a recess (5) in a second planar element (2) into which the protrusion (3) of the first planar element (1) is insertable, and a securing element (6) which is interlockingly insertable into the opening (4) of the protrusion (3).

Abstract: A learning model is trained for rate-distortion behavior prediction against a corpus of a video hosting platform and used to determine optimal bitrate allocations for video data given video content complexity across the corpus of the video hosting platform. Complexity features of the video data are processed using the learning model to determine a rate-distortion cluster prediction for the video data, and transcoding parameters for transcoding the video data are selected based on that prediction. The rate-distortion clusters are modeled during the training of the learning model, such as based on rate-distortion curves of video data of the corpus of the video hosting platform and based on classifications of such video data. This approach minimizes total corpus egress and/or storage while further maintaining uniformity in the delivered quality of videos by the video hosting platform.

Abstract: Bitrate-adaptive segmentation is performed for transcoding a video stream uploaded to an online video platform for hosting and later playback to platform users. The video stream is segmented into chunks based on prediction-based bit costs determined for frames of the video stream rather than based on scene changes detected within the video stream. The bitrate-adaptive segmentation includes determining inter-prediction bit costs and intra-prediction bit costs for frames of the video stream based on information indicated within a pass log based on a first pass encoding of the video stream, determining chunk boundaries for segmenting the video stream into a chunk based on the inter-prediction bit costs and the intra-prediction bit costs for the frames, and transcoding the chunk to produce a transcoded video stream.

Abstract: A learning model is trained for rate-distortion behavior prediction against a corpus of a video hosting platform and used to determine optimal bitrate allocations for video data given video content complexity across the corpus of the video hosting platform. Complexity features of the video data are processed using the learning model to determine a rate-distortion cluster prediction for the video data, and transcoding parameters for transcoding the video data are selected based on that prediction. The rate-distortion clusters are modeled during the training of the learning model, such as based on rate-distortion curves of video data of the corpus of the video hosting platform and based on classifications of such video data. This approach minimizes total corpus egress and/or storage while further maintaining uniformity in the delivered quality of videos by the video hosting platform.

Abstract: A cloud-based gaming server renders a set of game frames at a first frame rate for a current client gaming session. An encoder of the server then determines whether the first frame rate is lower than a second frame rate associated with the encoder. In response to the first frame rate being lower, the encoder is configured to generate skip frames, with each skip frame indicating that a game frame of the set of game frames is to be repeated. The encoder also encodes the set of game frames to produce a set of encoded game frames and inserts one or more skip frames between two or more encoded game frames of the set of encoded game frames to produce a game stream. The server then packetizes the game stream and transmits the packetized game stream to a client system associated with the current client system.

Abstract: Bitrate-adaptive segmentation is performed for transcoding a video stream uploaded to an online video platform for hosting and later playback to platform users. The video stream is segmented into chunks based on prediction-based bit costs determined for frames of the video stream rather than based on scene changes detected within the video stream. The bitrate-adaptive segmentation includes determining inter-prediction bit costs and intra-prediction bit costs for frames of the video stream based on information indicated within a pass log based on a first pass encoding of the video stream, determining chunk boundaries for segmenting the video stream into a chunk based on the inter-prediction bit costs and the intra-prediction bit costs for the frames, and transcoding the chunk to produce a transcoded video stream.

Abstract: Bitrate-adaptive segmentation is performed for transcoding a video stream uploaded to an online video platform for hosting and later playback to platform users. The video stream is segmented into chunks based on prediction-based bit costs determined for frames of the video stream rather than based on scene changes detected within the video stream. The bitrate-adaptive segmentation includes determining inter-prediction bit costs and intra-prediction bit costs for frames of the video stream based on information indicated within a pass log based on a first pass encoding of the video stream, determining chunk boundaries for segmenting the video stream into a chunk based on the inter-prediction bit costs and the intra-prediction bit costs for the frames, and transcoding the chunk to produce a transcoded video stream.

Abstract: A learning model is trained for rate-distortion behavior prediction against a corpus of a video hosting platform and used to determine optimal bitrate allocations for video data given video content complexity across the corpus of the video hosting platform. Complexity features of the video data are processed using the learning model to determine a rate-distortion cluster prediction for the video data, and transcoding parameters for transcoding the video data are selected based on that prediction. The rate-distortion clusters are modeled during the training of the learning model, such as based on rate-distortion curves of video data of the corpus of the video hosting platform and based on classifications of such video data. This approach minimizes total corpus egress and/or storage while further maintaining uniformity in the delivered quality of videos by the video hosting platform.

Abstract: A request for a video may be received from a client device. A determination whether to transmit the video at a first video resolution or a second video resolution based on a quality of the video at the first video resolution when converted to the second video resolution at the client device may be made. The video may be transmitted to the client device at the determined first video resolution or the second video resolution.

Abstract: Implementations disclose adaptive rate control technology that selects different encoders for different chunks of a media item based on the complexity of the individual chunks. A method includes accessing a media item comprising a first chunk and a second chunk; determining, by a processing device, a first media complexity measure for the first chunk and a second media complexity measure for the second chunk; selecting, by the processing device, a first encoder and a second encoder from a plurality of encoders, wherein the first encoder is selected based on the first media complexity measure of the first chunk and the second encoder is selected based on the second media complexity measure of the second chunk; and encoding the first chunk using the first encoder and encoding the second chunk using the second encoder.

Abstract: Systems and methods for processing a video sequence are disclosed. In accordance with some implementations, The method includes determining a first set of shot-change locations associated with a cut transition in a video sequence based on variance data defined in an encoding log associated with at least one previously encoded video frame. The method further includes determining a second set of shot-change locations associated with a fading transition in the video sequence based on the variance data defined in the encoding log associated with the at least one previously encoded video frame. The method also includes processing the video sequence based on at least a portion of the first set of shot-change locations and the second set of shot-change locations.

Abstract: Videos associated with video resolutions may be received. A first bitrate for each of the video resolutions may be identified based on a first bitrate point associated with the videos where a quality of the videos at a first video resolution that is upscaled to a second video resolution is better than a quality of the videos at the second video resolution at bitrates below the first bitrate point. The upscaling of the first video resolution may correspond to converting the videos from the first video resolution to the second video resolution at a client device. The identified corresponding first bitrate may be assigned to each of the video resolutions.

Abstract: Implementations disclose adaptive rate control technology that selects different encoders for different chunks of a media item based on the complexity of the individual chunks. A method includes accessing a media item comprising a first chunk and a second chunk; determining, by a processing device, a first media complexity measure for the first chunk and a second media complexity measure for the second chunk; selecting, by the processing device, a first encoder and a second encoder from a plurality of encoders, wherein the first encoder is selected based on the first media complexity measure of the first chunk and the second encoder is selected based on the second media complexity measure of the second chunk; and encoding the first chunk using the first encoder and encoding the second chunk using the second encoder.

Abstract: Systems and methods for processing a video sequence are disclosed. In accordance with some implementations, The method includes determining a first set of shot-change locations associated with a cut transition in a video sequence based on variance data defined in an encoding log associated with at least one previously encoded video frame. The method further includes determining a second set of shot-change locations associated with a fading transition in the video sequence based on the variance data defined in the encoding log associated with the at least one previously encoded video frame. The method also includes processing the video sequence based on at least a portion of the first set of shot-change locations and the second set of shot-change locations.

Abstract: A plurality of videos associated with a plurality of video resolutions may be received. A minimum bitrate may be identified for each of the video resolutions based on a first bitrate point associated with the videos where a quality of the videos at a first video resolution that is upscaled to a second video resolution is better than a quality of the videos at the second video resolution at bitrates below the first bitrate point. Furthermore, a maximum bitrate may be identified for each of the video resolutions based on a second bitrate point where the rate of change of the quality of the videos is below a threshold value. The identified minimum bitrates and the maximum bitrates may be assigned to the video resolutions.

Abstract: A system to facilitate analyzing and/or processing video content using encoding logs is provided. The system includes a first analysis component, a second analysis component and a transcoding component. The first analysis component determines a first set of shot-change locations associated with a cut transition in a video sequence based on an encoding log associated with at least one previously encoded video frame. The second analysis component determines a second set of shot-change locations associated with a fading transition in the video sequence based on the encoding log associated with the at least one previously encoded video frame. The transcoding component processes the video sequence based on at least a portion of the first set of shot-change locations and the second set of shot-change locations.

Abstract: The disclosed invention is a enhancement to the Video Encoder component of the MPEG standard to improve both the efficiency and quality of the video presentation at the display device. The inventions described below pertain to the enhancement of video compression technology. In general, they are compatible with MPEG video standards (as in current art), but represent novel enhancements thereof. The above inventions apply to several transmission media and networks including cable, DSL, wireless, satellite and IP networks. Another category of invention in this disclosure enhances networking performance by recognizing that the transmitted information is video, rather than data. This invention can be scaled to other classes of multimedia data such as speech or audio or images.

Abstract: The application describes a container, bag, pouch or envelope which has a first part and a second part, the container, bag, pouch or envelope being closed by the first part locating within the second part, the second part having a first opening for receiving the first part and a second opening for receiving the head of a breakable and disposable seal which locks into the first part in such a manner that it cannot be removed without breaking the seal, the seal in its inserted position locking the first part in place inside the second part in a tamper evident fashion.