DocumentCode :
495342
Title :
Effective Shot Segmentation Method Based on Rough Sets in Video Compressed Domain
Author :
Xiang-wei, Li ; Ming-xin, Zhang ; Lang-tao, Zhao ; Jin-hong, Xing ; Ya-lin, Zhu
Author_Institution :
Dept. of Comput. Eng., Lanzhou Polytech. Coll., Lanzhou, China
Volume :
6
fYear :
2009
fDate :
March 31 2009-April 2 2009
Firstpage :
421
Lastpage :
425
Abstract :
Based on rough sets (RS), an effective shot segmentation method is proposed in discrete cosine transform (DCT) compressed domain. First, DCT coefficients and DC coefficients are extracted from video sequences, and an information system is constructed with DC coefficient. Second, information system is reduced by reduction theory of RS, and the representation of the video frames is generated by reduced DC coefficients. Third, by introducing subdividing theory of RS, the frames of video are segmented scientifically. The experimental results show that the method can achieve good performance. Compared to conventional methods, the method enjoys following advantages. Firstly, only a subset of frames needs to be considered during analysis, allowing the reduction of the computational complexity, so the method can avoid the expensive computations in decompression processes. Secondly, the segmentation relativity of video shots becomes more scientific than previous methods. Its robustness and effectiveness are validated by experiments with various kinds of video sequences.
Keywords :
computational complexity; discrete cosine transforms; image segmentation; image sequences; rough set theory; video coding; computational complexity; decompression processes; discrete cosine transform; information system; rough sets; shot segmentation method; video compressed domain; video sequences; Color; Discrete cosine transforms; Educational institutions; Event detection; Gunshot detection systems; Information systems; Motion detection; Rough sets; Video compression; Video sequences; compressed domain; rough sets; shot;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
Type :
conf
DOI :
10.1109/CSIE.2009.304
Filename :
5170733
Link To Document :
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