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Author:

Deng, Zhipin (Deng, Zhipin.) | Jia, Kebin (Jia, Kebin.) (Scholars:贾克斌) | Zhuang, Xinyue (Zhuang, Xinyue.)

Indexed by:

EI Scopus

Abstract:

The proliferation of video content makes video similarity detection an indispensable tool in video management, searching, and navigation. In this paper, a novel video retrieval algorithm targeted on detecting given video clips from TV programs is proposed. The algorithm has the following two advantages. Firstly, the video spatiotemporal feature used in this algorithm has many favorable features, such as easily and uniquely extraction, and drastically video information reduction. Secondly, the algorithm is robust against the whole offset of color or brightness and abrupt intense disturbance, which are frequently seen on TV programs. Grads comparison method and Exception Factor were introduced to enhance algorithm robustness. Experimental results demonstrated the effectiveness of the algorithm.

Keyword:

Wireless sensor networks Content based retrieval Feature extraction Extraction Gradient methods

Author Community:

  • [ 1 ] [Deng, Zhipin]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100022, China
  • [ 2 ] [Jia, Kebin]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100022, China
  • [ 3 ] [Zhuang, Xinyue]School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100022, China

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Source :

Year: 2007

Issue: 533 CP

Page: 652-655

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 13

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