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作者:

Dong, Pei (Dong, Pei.) | Xia, Yong (Xia, Yong.) | Feng, David Dagan (Feng, David Dagan.)

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EI Scopus

摘要:

Video summarization enables convenient and efficient management of large volume of visual data. However, most existing summarization approaches are based on either the pixel domain information or conventional video compression standards. As the most recent and popular international video coding standard, H.264/AVC adopts a number of advanced techniques and brings not only opportunities but also challenges to video summarization. In this paper, we propose a real-time image storyboard generation algorithm for H.264/AVC compressed videos by using both compressed domain and pixel domain information jointly and adaptively. This algorithm extracts compressed domain information for visual content representation, video structuring and candidate representative frame selection. By fusing both compressed domain and pixel domain information, the redundancy in the candidate representative frames is further reduced. Our experimental results show that the proposed algorithm can efficiently produce image storyboards conforming to human interpretation of the essential content in generic videos. © 2012 IEEE.

关键词:

Image coding Image compression Motion Picture Experts Group standards Pixels Video recording Video signal processing

作者机构:

  • [ 1 ] [Dong, Pei]Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, NSW 2006, Australia
  • [ 2 ] [Dong, Pei]Signal and Information Processing Laboratory, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Xia, Yong]Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, NSW 2006, Australia
  • [ 4 ] [Feng, David Dagan]Biomedical and Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, NSW 2006, Australia

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ISSN: 1945-7871

年份: 2012

页码: 544-549

语种: 英文

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WoS核心集被引频次: 0

SCOPUS被引频次: 2

ESI高被引论文在榜: 0 展开所有

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