Netflix Inc.

Kyle Christopher Swanson

Liwei Guo

Anne Aaron

Jan De Cock

Sonia Bhaskar

Glenn Van Wallendael

Xiaoqing Zhu

Anush Moorthy

Aditya Mavlankar

Te-Yuan Huang

Li-Heng Chen

Adithya Prakash

Sagar Bharadwaj Kalasibail Seetharam

Renata Cruz Teixeira

Kaylie Alexa Kwon

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 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.

Simulation-based techniques for evaluating encoding ladders for video streaming

In various embodiments, a video editing application receives, from an encoding application, a list of random access points of an encoded media content item. When an operator specifies a point of interest for the media content item, the video editing application determines a closest random access point to the point of interest and modifies the point of interest to coincide with the closest random access point. The encoding application can also modify the point of interest to coincide with an existing random access point if the point of interest is within a tolerance of the existing random access point and the point of interest is not frame specific. Further, the encoding application can modify media metrics, computed using pre-encoded versions of the media content item, using heuristics to account for operator-specified points of interest that do not coincide with, or are not within a tolerance of, existing random access points.

Techniques for avoiding re-encoding of media content items

In various embodiments, an interpolation-based encoding application encodes a first subsequence included in a media title at each encoding point included in a first set of encoding points to generate encoded subsequences. Subsequently, the interpolation-based encoding application performs interpolation operation(s) based on the encoded subsequences to estimate a first media metric value associated with a first encoding point that is not included in the first set of encoding points. The interpolation-based encoding application then generates an encoding recipe based on the encoded subsequences and the first media metric value. The encoding recipe specifies a different encoding point for each subsequence included in the media title. After determining that the encoding recipe specifies the first encoding point for the first subsequence, the interpolation-based encoding application encodes the first subsequence at the first encoding point to generate at least a portion of an encoded version of the media title.

Techniques for efficiently performing subsequence-based encoding for a media title

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Los Gatos, CA, United States of America

Kyle Christopher Swanson