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    TECHNIQUES FOR ROBUSTLY PREDICTING PERCEPTUAL VIDEO QUALITY
    2.
    发明申请
    TECHNIQUES FOR ROBUSTLY PREDICTING PERCEPTUAL VIDEO QUALITY 审中-公开
    强大的预测知名视频质量的技术

    公开(公告)号：WO2017176656A1

    公开(公告)日：2017-10-12

    申请号：PCT/US2017/025801

    申请日：2017-04-03

    Applicant: NETFLIX, INC.

    Inventor： AARON, Anne ,  LI, Zhi ,  GOODALL, Todd

    IPC: H04N19/00

    Abstract: In various embodiments, a quality trainer trains a model that computes a value for a perceptual video quality metric for encoded video content. During a pre-training phase, the quality trainer partitions baseline values for metrics that describe baseline encoded video content into partitions based on genre. The quality trainer then performs cross-validation operations on the partitions to optimize hyperparameters associated with the model. Subsequently, during a training phase, the quality trainer performs training operations on the model that includes the optimized hyperparameters based on the baseline values for the metrics to generate a trained model. The trained model accurately tracks the video quality for the baseline encoded video content. Further, because the cross-validation operations minimize any potential overfitting, the trained model accurately and consistently predicts perceived video quality for non-baseline encoded video content across a wide range of genres.

    Abstract translation: 在各种实施例中，质量培训师训练计算经编码的视频内容的感知视频质量度量的值的模型。 在预培训阶段，质量培训师根据流派将基准编码视频内容描述的分割基准值分割成分区。 质量培训师然后对分区执行交叉验证操作，以优化与模型相关联的超参数。 随后，在训练阶段期间，质量训练师基于该度量的基线值对包括优化超参数的模型执行训练操作以生成训练模型。 训练好的模型准确地跟踪基线编码的视频内容的视频质量。 此外，由于交叉验证操作使任何潜在的过度拟合最小化，所以经过训练的模型准确且一致地预测跨广泛流派的非基线编码视频内容的感知视频质量。

    TECHNIQUES FOR INCREASING THE ACCURACY OF SUBJECTIVE QUALITY EXPERIMENTS
    3.
    发明申请
    TECHNIQUES FOR INCREASING THE ACCURACY OF SUBJECTIVE QUALITY EXPERIMENTS 审中-公开

    公开(公告)号：WO2022026792A1

    公开(公告)日：2022-02-03

    申请号：PCT/US2021/043836

    申请日：2021-07-30

    Applicant: NETFLIX, INC.

    Inventor： LI, Zhi

    IPC: H04N21/466

    Abstract: In various embodiments, a data optimization application mitigates scoring inaccuracies in subjective quality experiments. In operation, the data optimization application generates a model that includes a first set of individual scores and a first set of parameters. The first set of parameters includes a first subjective score set and a first set of subjective factor sets. The data optimization application performs one or more optimization operations on the first set of parameters to generate a second set of parameters. The second set of parameters includes a second subjective score set and a second set of subjective factor sets, wherein the second subjective score set compensates for at least a first subjective factor set included in the second set of subjective factor sets. The data optimization application also computes a participant evaluation report based on at least a second subjective factor setsincluded in the second set of subjective factor sets.

    TECHNIQUES FOR DETERMINING AN UPPER BOUND ON VISUAL QUALITY OVER A COMPLETED STREAMING SESSION
    4.
    发明申请
    TECHNIQUES FOR DETERMINING AN UPPER BOUND ON VISUAL QUALITY OVER A COMPLETED STREAMING SESSION 审中-公开

    公开(公告)号：WO2020018465A1

    公开(公告)日：2020-01-23

    申请号：PCT/US2019/041889

    申请日：2019-07-15

    Applicant: NETFLIX, INC.

    Inventor： LI, Zhi ,  HUANG, Te-Yuan

    IPC: H04N21/2343 ,  H04N21/234 ,  H04N21/24 ,  H04N21/44

    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.

    SOURCE-CONSISTENT TECHNIQUES FOR PREDICTING ABSOLUTE PERCEPTUAL VIDEO QUALITY
    7.
    发明申请
    SOURCE-CONSISTENT TECHNIQUES FOR PREDICTING ABSOLUTE PERCEPTUAL VIDEO QUALITY 审中-公开

    公开(公告)号：WO2018111655A1

    公开(公告)日：2018-06-21

    申请号：PCT/US2017/064975

    申请日：2017-12-06

    Applicant: NETFLIX, INC.

    Inventor： LI, Zhi ,  AARON, Anne ,  MOORTHY, Anush ,  BAMPIS, Christos

    IPC: H04N19/154 ,  H04N19/59 ,  H04N19/00

    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.

    TECHNIQUES FOR EVALUATING A VIDEO RATE SELECTION ALGORITHM OVER A COMPLETED STREAMING SESSION
    8.
    发明申请
    TECHNIQUES FOR EVALUATING A VIDEO RATE SELECTION ALGORITHM OVER A COMPLETED STREAMING SESSION 审中-公开

    公开(公告)号：WO2019226481A1

    公开(公告)日：2019-11-28

    申请号：PCT/US2019/032863

    申请日：2019-05-17

    Applicant: NETFLIX, INC.

    Inventor： HUANG, Te-Yuan ,  EKANADHAM, Chaitanya ,  BERGLUND, Andrew J. ,  LI, Zhi

    IPC: H04N19/184 ,  H04N21/2343 ,  H04N21/845

    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 GENERATING PER-TITLE ENCODING LADDERS
    9.
    发明申请
    TECHNIQUES FOR GENERATING PER-TITLE ENCODING LADDERS 审中-公开

    公开(公告)号：WO2022173687A1

    公开(公告)日：2022-08-18

    申请号：PCT/US2022/015455

    申请日：2022-02-07

    Applicant: NETFLIX, INC.

    Inventor： MOORTHY, Anush ,  LI, Zhi ,  GUO, Liwei ,  MAVLANKAR, Aditya ,  AARON, Anne

    IPC: H04N21/234 ,  H04N19/10 ,  H04N21/2343 ,  H04N21/2662 ,  H04N21/845

    Abstract: In various embodiments, an encoding ladder application generates encoding ladders for encoding media titles. In operation, the encoding ladder application generates a first convex hull representing encoding tradeoffs between quality and bitrate when encoding a media title at a first resolution. The encoding ladder application generates a second convex hull representing encoding tradeoffs between quality and bitrate when encoding the media title at a second resolution. Based on the first convex hull and the second convex hull, the encoding ladder application generates an overall convex hull. Subsequently, the encoding ladder application generates an encoding ladder for the media title based on at least the overall convex hull and a ladder requirement. Advantageously, the tradeoffs between quality and bitrate represented by the encoding ladder are customized for the media title. Consequently, encoding inefficiencies attributable to conventional fixed-bitrate ladders can be reduced.

    QUANTIFYING PERCEPTUAL QUALITY MODEL UNCERTAINTY VIA BOOTSTRAPPING
    10.
    发明申请
    QUANTIFYING PERCEPTUAL QUALITY MODEL UNCERTAINTY VIA BOOTSTRAPPING 审中-公开

    公开(公告)号：WO2019183280A1

    公开(公告)日：2019-09-26

    申请号：PCT/US2019/023256

    申请日：2019-03-20

    Applicant: NETFLIX, INC.

    Inventor： BAMPIS, Christos ,  LI, Zhi ,  SHARAN, Lavanya ,  NOVAK, Julie ,  TINGLEY, Martin

    IPC: H04N21/25 ,  G06K9/62 ,  H04N17/00 ,  H04N19/147 ,  H04N19/154 ,  G06N20/20

    Abstract: In various embodiments, a bootstrapping training subsystem performs sampling operation(s) on a training database that includes subjective scores to generate resampled dataset. For each resampled dataset, the bootstrapping training subsystem performs machine learning operation(s) to generate a different bootstrap perceptual quality model. The bootstrapping training subsystem then uses the bootstrap perceptual quality models to quantify the accuracy of a perceptual quality score generated by a baseline perceptual quality model for a portion of encoded video content. Advantageously, relative to prior art solutions in which the accuracy of a perceptual quality score is unknown, the bootstrap perceptual quality models enable developers and software applications to draw more valid conclusions and/or more reliably optimize encoding operations based on the perceptual quality score.

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