Netflix Inc.

Adithya Prakash

Rohit Puri

Anush Moorthy

Aditya Mavlankar

Liwei Guo

Li-Heng Chen

Kyle Christopher Swanson

Thomas E Mack

Shinjan Tiwary

Subhabrata Bhattacharya

Abhishek Soni

Shraddha Ladda

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

The disclosed computer-implemented method may include accessing defect identification data that identifies defects in frames of video content. The method may also include generating, as part of the interactive user interface, an interactive element that presents the frames of video content. The method may further include generating, as part of the interactive user interface, another interactive element that presents selectable metadata items associated with the identified defects in the frames of video content. At least one of the selectable metadata items may include an associated user interface action. Then, upon receiving an input selecting one of the selectable metadata items, the method may include performing the associated user interface action. Various other methods, systems, and computer-readable media are also disclosed.

Interactive interface for identifying defects in video content

In various embodiments, a defective pixel detection application automatically detects defective pixels in video content. In operation, the defective pixel detection application computes a first set of pixel intensity gradients based on a first frame of video content and a first neighborhood of pixels associated with a first pixel. The defective pixel detection application also computes a second set of pixel intensity gradients based on the first frame and a second neighborhood of pixels associated with the first pixel. Subsequently, the defective pixel detection application computes a statistical distance between the first set of pixel intensity gradients and the second set of pixel intensity gradients. The defective pixel detection application then determines that the first pixel is defective based on the statistical distance.

Techniques for detecting spatial anomalies in video content

One embodiment of the present invention sets forth a technique for detecting a shot change in a video. The technique includes calculating a first plurality of difference values for pixel blocks included in a first video frame and a second video frame and calculating a first cumulative distribution function (CDF) based on the first plurality of difference values. The technique further includes calculating a second plurality of difference values for pixel blocks included in a first plurality of video frames that is contiguous with the first video frame and calculating a second CDF based on the second plurality of difference values. The technique further includes comparing the first CDF to the second CDF to detect a shot change.

Detecting shot changes in a video

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Campbell, CA, United States of America

Adithya Prakash