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Automated workflows from media asset differentials

專利號
US11659214B2
公開日期
2023-05-23
申請人
Netflix, Inc.(US CA Los Gatos)
發(fā)明人
Yadong Wang; Chih-Wei Wu; Kyle Tacke; Shilpa Jois Rao; Boney Sekh; Andrew Swan; Raja Ranjan Senapati
IPC分類
H04N21/2343; G11B27/10; G11B27/031; H04N21/234; G06Q10/0631
技術(shù)領(lǐng)域
media,edits,content,temporally,data,segments,may,sequenced,workflow,object
地域: CA CA Los Gatos

摘要

The disclosed computer-implemented method may include (1) accessing a first media data object and a different, second media data object that, when played back, each render temporally sequenced content, (2) comparing first temporally sequenced content represented by the first media data object with second temporally sequenced content represented by the second media data object to identify a set of common temporal subsequences between the first media data object and the second media data object, (3) identifying a set of edits relative to the set of common temporal subsequences that describe a difference between the temporally sequenced content of the first media data object and the temporally sequenced content of the second media data object, and (4) executing a workflow relating to the first media data object and/or the second media data object based on the set of edits. Various other methods, systems, and computer-readable media are also disclosed.

說明書

One method for determining modifications between two versions of the same media asset may involve the detection of common subsequences shared by both media assets. A suitable longest audio common subsequence (LACS) algorithm or longest video common subsequence (LVCS) algorithm may be used to identify common subsequences. By mapping common subsequences shared by media assets, additions, deletions, substitutions, changes to order, etc. may be determined. Various features may be used when comparing the individual subsequences within two media assets. In some examples, for audio assets, spectrograms (e.g., log-mel spectrograms) may be used. In some examples, for video assets, reduced-resolution frames may be used. Comparisons may be computed using a suitable distance function (e.g., a standardized Euclidian distance or a mean squared error (MSE)). Once a pairwise comparison matrix that includes comparisons of the individual subsequences in two media assets has been computed, an optimal path may be read from the table that indicates the longest common subsequences shared by the media assets and/or indications of differences between the media assets.

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