Abstract: In some embodiments, an image is received. The method includes analyzing the image based on a plurality of anchor shapes to generate respective outputs for anchor shapes in the plurality of anchor shapes. The output rates a cropping of the image using a respective anchor shape. The method analyzes respective outputs for the anchor shapes in the plurality of anchor shapes to select an anchor shape. The image is cropped using the anchor shape.

Abstract: In some embodiments, a method calculates a reward function for an adaptive bitrate function that is based on a bandwidth and profiles in a profile ladder for a current segment of content. The reward function calculates a first profile should be selected for the current segment and, based on a previously selected profile from a prior segment and profiles in the profile ladder, changes the first profile to a second profile from the profile ladder. The method requests the second profile from the profile ladder for the current segment.

Abstract: In some embodiments, a method generates a first representation of a first relationship between bitrate and quality based on first features of a first portion of a video. The first representation is analyzed to determine a first list of potential bitrates for the first portion of video. The method analyzes potential bitrates and quality associated with the respective potential bitrates to refine the first list of potential bitrates to a second list of bitrates. The second list of bitrates includes a different list of bitrates than the first list of potential bitrates. The method outputs the second list of bitrates for encoding the first portion of video.

Abstract: In some embodiments, a method receives quality metric values for profile levels in a plurality of profile levels for a segment of content. An available bandwidth and associated bitrates of profile levels in the plurality of profile levels are evaluated to select a first profile level. The quality metric values for profile levels in the plurality of profile levels are evaluated to select a second profile level. The method selects a profile level in the plurality of profile levels based on the first profile level and the second profile level. The profile level that is selected is requested for the segment.

Abstract: In some embodiments, a method receives a first image and a second image for a comparison of film grain. The first image and the second image are converted from a spatial domain to a frequency domain to generate a first frequency domain representation for the first image and a second frequency domain representation of the second image. The method compares a first distribution of frequency components from the first frequency domain representation to a second distribution of frequency components from the second frequency domain representation. A score for an assessment of differences of the film grain in the first image and the second image is generated based on the comparing.

Abstract: In some embodiments, a method analyzes flagged locations from a plurality of locations in an encoding of a video to form a cluster of locations. Draft micro-chunk boundaries for the cluster are determined based on searching for a first start location and a first end location in the encoding. The method searches in a first search range before the first start location and a second search range after the first end location for a second start location in the first search range and a second end location in the second search range. The second start location and the second end location form a micro-chunk. An encoding parameter set is determined for the micro-chunk formed by the second start location and the second end location based on content characteristics of the micro-chunk. The method uses the encoding parameter set to encode the micro-chunk for insertion in the encoding of the video.

Abstract: In some embodiments, a method receives a data structure for an auto decision process for predicting a value for a decision feature of a plurality of features. The data structure is generated using a decision aware splitting process that splits a node in the data structure using the decision feature and a metric-based process that splits other nodes of the data structure by evaluating features in the plurality of features using a metric. Feature values are determined for a combination of features for a playback session. The method evaluates the data structure using the combination of features to determine a plurality of prediction values for a plurality of feature values of the decision feature. The prediction values are used to generate a decision for the playback session by selecting a feature value in the plurality of feature values based on the plurality of prediction values.

Abstract: In some embodiments, a grain analysis system is configured for analyzing a first video frame and outputting respective first film grain information for film grain that is included in the first video frame or configured for analyzing a second video frame and outputting second film grain information. At least one of a grain removal system and a grain synthesis system is included. The grain removal system is configured for removing the film grain from the first video frame using the first film grain information to generate a third video frame corresponding to the first video frame with film grain removed. The grain analysis system is separate from the grain removal system. The grain synthesis system is configured for synthesizing film grain for the third video frame using the first film grain information or the second film grain information. The grain analysis system is separate from the grain synthesis system.

Abstract: In some embodiments, a method analyzes a characteristic of a segment list for a user identifier, and compares the characteristic for the segment list to two or more thresholds. A storage type is determined for the segment list based on the comparing. A value for the segment list is stored using a storage type from a plurality of storage types based on the characteristic for the segment list meeting a threshold for the storage type from the two or more storage types. The method stores the value for the segment list in storage, wherein the value is stored based on the storage type.

Abstract: In some embodiments, a method generates a first representation of a first relationship between bitrate and quality based on first features of a first portion of a video. Also, the method generates a second representation of a second relationship between bitrate and quality based on second features of a second portion of a video. The first representation is analyzed to determine a first list of bitrates for the first portion of video and the second representation is analyzed to determine a second list of bitrates for the second portion of video. The first list of bitrates is different from the second list of bitrates. The method outputs the first list of bitrates for use encoding the first portion of video and the second list of bitrates for use encoding the second portion of video.

Abstract: One embodiment of the present invention sets forth a technique for inserting content into a media program. The technique includes determining a plurality of markers corresponding to a plurality of locations within a media program. The technique also includes for each marker included in the plurality of markers, automatically analyzing a first set of intervals within the media program that lead up to the marker and a second set of intervals within the media program that immediately follow the marker and determine a set of audio characteristics associated with the first set of intervals and the second set of intervals. The technique further includes generating a plurality of scores for the plurality of markers based on the set of audio characteristics for each marker and inserting additional content at one or more markers included in the plurality of markers based on the plurality of scores.

Abstract: In some embodiments, a method generates a reward function for an adaptive bitrate function that is based on a bandwidth and profiles in a profile ladder for a current segment of content. The reward function indicates a first profile should be selected for the current segment. The method performs a quality change analysis to select a second profile from the profile. The quality change analysis analyzes a quality change that is based on a previously selected profile from a prior segment and profiles in the profile ladder. The second profile is requested from the profile ladder for the current segment.

Abstract: In some embodiments, a method generates a reward function for an adaptive bitrate function that is based on a bandwidth and profiles in a profile ladder for a current segment of content. The reward function indicates a first profile should be selected for the current segment. The method performs a quality change analysis to select a second profile from the profile. The quality change analysis analyzes a quality change that is based on a previously selected profile from a prior segment and profiles in the profile ladder. The second profile is requested from the profile ladder for the current segment.

Abstract: In some embodiments, a method segments a frame of a video into a plurality of regions and classifies a region in the plurality of regions with a region type in a plurality of region types. Film grain synthesis information is generated for the region in the plurality of regions based on the region type that is associated with the region. The method outputs the film grain synthesis information for adding film grain to the region of the frame.