research-article

Video browsing system based on compressed domain feature extraction

Authors:

A. Divakaran,

A. Vetro,

K. Asai,

H. NishikawaAuthors Info & Claims

IEEE Transactions on Consumer Electronics, Volume 46, Issue 3

Pages 637 - 644

https://doi.org/10.1109/30.883424

Published: 01 August 2000 Publication History

Abstract

We present a video browsing system that dynamically extracts features and other content-description (meta-data) from compressed video. We devise a description scheme for a video browsing system that combines color and motion descriptors extracted in the compressed domain. The extraction is fast and enables our proposed dynamic feature extraction based video browsing system. We examine the tradeoff between fast feature extraction and accuracy of matching to arrive at a combination of color and motion descriptors that is easy to extract and provides accurate matching

Cited By

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Rahmani FZargari F(2017)Compressed domain visual information retrieval based on I-frames in HEVCMultimedia Tools and Applications10.1007/s11042-016-3391-576:5(7283-7300)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1007/s11042-016-3391-5
Mehrabi MZargari FGhanbari M(2012)Compressed domain content based retrieval using H.264 DC-picturesMultimedia Tools and Applications10.1007/s11042-010-0597-960:2(443-453)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1007/s11042-010-0597-9
Doulamis NDoulamis A(2005)Non-sequential multiscale content-based video decompositionSignal Processing10.1016/j.sigpro.2004.10.00485:2(325-356)Online publication date: 1-Feb-2005
https://dl.acm.org/doi/10.1016/j.sigpro.2004.10.004
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Video browsing system based on compressed domain feature extraction
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
  2. Machine learning
    1. Machine learning algorithms

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cover image IEEE Transactions on Consumer Electronics

IEEE Transactions on Consumer Electronics Volume 46, Issue 3

August 2000

527 pages

ISSN:0098-3063

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IEEE Press

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Published: 01 August 2000

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Rahmani FZargari F(2017)Compressed domain visual information retrieval based on I-frames in HEVCMultimedia Tools and Applications10.1007/s11042-016-3391-576:5(7283-7300)Online publication date: 1-Mar-2017
https://dl.acm.org/doi/10.1007/s11042-016-3391-5
Mehrabi MZargari FGhanbari M(2012)Compressed domain content based retrieval using H.264 DC-picturesMultimedia Tools and Applications10.1007/s11042-010-0597-960:2(443-453)Online publication date: 1-Sep-2012
https://dl.acm.org/doi/10.1007/s11042-010-0597-9
Doulamis NDoulamis A(2005)Non-sequential multiscale content-based video decompositionSignal Processing10.1016/j.sigpro.2004.10.00485:2(325-356)Online publication date: 1-Feb-2005
https://dl.acm.org/doi/10.1016/j.sigpro.2004.10.004
Lee DErol BGraham JHull JMurata NRowe LMerialdo BMuhlhauser MRoss KDimitrova N(2002)Portable meeting recorderProceedings of the tenth ACM international conference on Multimedia10.1145/641007.641111(493-502)Online publication date: 1-Dec-2002
https://dl.acm.org/doi/10.1145/641007.641111

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Genetic-Based Type II Feature Extraction for Periocular Biometric Recognition: Less is More

Kernel-based feature extraction under maximum margin criterion

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