TECHNIQUES FOR OPTIMIZING ENCODING TASKS

    公开(公告)号:US20210127123A1

    公开(公告)日:2021-04-29

    申请号:US17141067

    申请日:2021-01-04

    Applicant: NETFLIX, INC.

    Abstract: In various embodiments, a shot collation application causes multiple encoding instances to encode a source video sequence that includes at least two shot sequences. The shot collation application assigns a first shot sequence to a first chunk. Subsequently, the shot collation application determines that a second shot sequence does not meet a collation criterion with respect to the first chunk. Consequently, the shot collation application assigns the second shot sequence or a third shot sequence derived from the second shot sequence to a second chunk. The shot collation application causes a first encoding instance to independently encode each shot sequence assigned to the first chunk. Similarly, the shot collation application causes a second encoding instance to independently encode each shot sequence assigned to the second chunk. Finally, a chunk assembler combines the first encoded chunk and the second encoded chunk to generate an encoded video sequence.

    SOURCE-CONSISTENT TECHNIQUES FOR PREDICTING ABSOLUTE PERCEPTUAL VIDEO QUALITY

    公开(公告)号:US20180167619A1

    公开(公告)日:2018-06-14

    申请号:US15782586

    申请日:2017-10-12

    Applicant: NETFLIX, INC.

    Abstract: In various embodiments, a perceptual quality application computes an absolute quality score for encoded video content. In operation, the perceptual quality application selects a model based on the spatial resolution of the video content from which the encoded video content is derived. The model associates a set of objective values for a set of objective quality metrics with an absolute quality score. The perceptual quality application determines a set of target objective values for the objective quality metrics based on the encoded video content. Subsequently, the perceptual quality application computes the absolute quality score for the encoded video content based on the selected model and the set of target objective values. Because the absolute quality score is independent of the quality of the video content, the absolute quality score accurately reflects the perceived quality of a wide range of encoded video content when decoded and viewed.

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