TECHNIQUES FOR DETERMINING AN UPPER BOUND ON VISUAL QUALITY OVER A COMPLETED STREAMING SESSION

    公开(公告)号:US20210160301A1

    公开(公告)日:2021-05-27

    申请号:US17164523

    申请日:2021-02-01

    Applicant: NETFLIX, INC.

    Abstract: In various embodiments, a hindsight application computes a hindsight metric value for evaluation of a video rate selection algorithm. The hindsight application determines a first encoding option associated with a source chunk of a media title based on a network throughput trace and a buffer trellis. The hindsight application determines that the first encoding option is associated with a buffered duration range. The buffered duration range is also associated with a second encoding option that is stored in the buffer trellis. After determining that the first encoding option is associated with a higher visual quality than the second encoding option, the hindsight application stores the first encoding option instead of the second encoding option in the buffer trellis to generate a modified buffer trellis. Finally, the hindsight application computes a hindsight metric value associated with a sequence of encoded chunks of the media title based on the modified buffer trellis.

    CONSTRAINED OPTIMIZATION TECHNIQUES FOR GENERATING ENCODING LADDERS FOR VIDEO STREAMING

    公开(公告)号:US20240244224A1

    公开(公告)日:2024-07-18

    申请号:US18154680

    申请日:2023-01-13

    Applicant: NETFLIX, INC.

    CPC classification number: H04N19/146 H04N19/105

    Abstract: In various embodiments, an encoding ladder application generates encoding ladders that are used to stream media titles. The encoding ladder application generates an objective function based on a ladder configuration and a parameterized objective function. The parameterized objective function approximates a tradeoff between a quality of experience and a cost term associated with a candidate encoding ladder. The encoding ladder application generates constraints based on the ladder configuration and parameterized constraints. The encoding ladder application executes a constrained optimization algorithm on the objective function, the constraints, and encoding point metadata associated with a set of encoded videos to generate a first candidate encoding ladder for a media title.

    TECHNIQUES FOR DETERMINING AN UPPER BOUND ON VISUAL QUALITY OVER A COMPLETED STREAMING SESSION

    公开(公告)号:US20200021634A1

    公开(公告)日:2020-01-16

    申请号:US16036600

    申请日:2018-07-16

    Applicant: NETFLIX, INC.

    Abstract: In various embodiments, a hindsight application computes a hindsight metric value for evaluation of a video rate selection algorithm. The hindsight application determines a first encoding option associated with a source chunk of a media title based on a network throughput trace and a buffer trellis. The hindsight application determines that the first encoding option is associated with a buffered duration range. The buffered duration range is also associated with a second encoding option that is stored in the buffer trellis. After determining that the first encoding option is associated with a higher visual quality than the second encoding option, the hindsight application stores the first encoding option instead of the second encoding option in the buffer trellis to generate a modified buffer trellis. Finally, the hindsight application computes a hindsight metric value associated with a sequence of encoded chunks of the media title based on the modified buffer trellis.

    SIMULATION-BASED TECHNIQUES FOR EVALUATING ENCODING LADDERS FOR VIDEO STREAMING

    公开(公告)号:US20240244281A1

    公开(公告)日:2024-07-18

    申请号:US18154709

    申请日:2023-01-13

    Applicant: NETFLIX, INC.

    CPC classification number: H04N21/64738 H04N21/238 H04N21/84

    Abstract: In various embodiments, a simulation evaluation application generates a first streaming header based on rungs of a first candidate encoding ladder, where each rung specifies a resolution and a bitrate of a different encoded video. The simulation evaluation application executes an adaptive bitrate algorithm on the first streaming header based on a network throughput trace to determine a first value for a metric that is relevant to quality of experience. The simulation evaluation application generates a second streaming header based on a second candidate encoding ladder. The simulation evaluation application executes the adaptive bitrate algorithm on the second streaming header based on the network throughput trace to determine a second value for the first metric. The simulation evaluation application compares the first value to the second value to determine that the first candidate encoding ladder instead of the second candidate encoding ladder should be used to stream the media title.

    TECHNIQUES FOR EVALUATING A VIDEO RATE SELECTION ALGORITHM BASED ON A GREEDY OPTIMIZATION OF TOTAL DOWNLOAD SIZE OVER A COMPLETED STREAMING SESSION

    公开(公告)号:US20210092178A1

    公开(公告)日:2021-03-25

    申请号:US17113884

    申请日:2020-12-07

    Applicant: NETFLIX, INC.

    Abstract: In various embodiments, a hindsight application computes a total download size for a sequence of encoded chunks associated with a media title for evaluation of at least one aspect of a video streaming service. The hindsight application computes a feasible download end time associated with a source chunk of the media title based on a network throughput trace and a subsequent feasible download end time associated with a subsequent source chunk of the media title. The hindsight application then selects an encoded chunk associated with the source chunk based on the network throughput trace, the feasible download end time, and a preceding download end time associated with a preceding source chunk of the media title. Subsequently, the hindsight application computes the total download size based on the number of encoded bits included in the first encoded chunk. The total download size correlates to an upper bound on visual quality.

    TECHNIQUES FOR EVALUATING A VIDEO RATE SELECTION ALGORITHM OVER A COMPLETED STREAMING SESSION

    公开(公告)号:US20190364084A1

    公开(公告)日:2019-11-28

    申请号:US16036606

    申请日:2018-07-16

    Applicant: NETFLIX, INC.

    Abstract: In various embodiments, a hindsight application computes a total download size for a sequence of encoded chunks associated with a media title for evaluation of at least one aspect of a video streaming service. The hindsight application computes a feasible download end time associated with a source chunk of the media title based on a network throughput trace and a subsequent feasible download end time associated with a subsequent source chunk of the media title. The hindsight application then selects an encoded chunk associated with the source chunk based on the network throughput trace, the feasible download end time, and a preceding download end time associated with a preceding source chunk of the media title. Subsequently, the hindsight application computes the total download size based on the number of encoded bits included in the first encoded chunk. The total download size correlates to an upper bound on visual quality.

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