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IEEE Transactions on Image Processing
Article . 2020 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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Fast Optical Flow Extraction From Compressed Video

Authors: Sean I. Young; Bernd Girod; David Taubman;

Fast Optical Flow Extraction From Compressed Video

Abstract

We propose the fast optical flow extractor, a filtering method that recovers artifact-free optical flow fields from HEVCcompressed video. To extract accurate optical flow fields, we form a regularized optimization problem that considers the smoothness of the solution and the pixelwise confidence weights of an artifactridden HEVC motion field. Solving such an optimization problem is slow, so we first convert the problem into a confidence-weighted filtering task. By leveraging the already-available HEVC motion parameters, we achieve a 100-fold speed-up in the running times compared to similar methods, while producing subpixel-accurate flow estimates. Je fast optical flow extractor is useful when video frames are already available in coded formats. Our method is not specific to a coder, and works with motion fields from video coders such as H.264/AVC and HEVC.

Country
Australia
Related Organizations
Keywords

anzsrc-for: 1702 Cognitive Sciences, 46 Information and Computing Sciences, augmented reality and games, anzsrc-for: 46 Information and Computing Sciences, anzsrc-for: 0801 Artificial Intelligence and Image Processing, anzsrc-for: 4607 Graphics, 4603 Computer Vision and Multimedia Computation, anzsrc-for: 4603 Computer Vision and Multimedia Computation, anzsrc-for: 0906 Electrical and Electronic Engineering, 004

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Average
Top 10%
Green