DocumentCode
498374
Title
Rough Sets Based Video Mining Preprocessing Algorithm in Compressed Domain
Author
Xiang-wei, Li ; Ming-xin, Zhang ; Ya-ling, Zhu ; Xing-du, Li ; Ting-bing, Ma
Author_Institution
Dept. of Comput. Eng., Lanzhou Polytech. Coll., Lanzhou, China
Volume
2
fYear
2009
fDate
19-21 May 2009
Firstpage
470
Lastpage
473
Abstract
A critical and fundamental task in video mining is data preprocessing, in this paper, aimed to overcome limitations of redundant data for video mining, the paper propose a video mining preprocessing algorithm based on Rough Sets. Firstly, the representative data of video sequences is extracted in compressed domain. Secondly, the Information System Table is constructed by extracted representative data. Finally, the Core of Information System Table is achieved by making use of the attributes reduction theory of RS. As our experimental results indicate, the algorithm can get effective and scientific data to complete video mining such as key frame extraction and shot segmentation and other operations. Compared to existing techniques, our proposed algorithm enjoys following advantages. (1) only a subset of frames need to be considered during video mining. (2) The limitations of requirements for a huge amount of memory and CPU resource are overcome.
Keywords
data mining; data reduction; rough set theory; video coding; attributes reduction theory; compressed domain; data preprocessing; information system table; key frame extraction; redundant data; rough sets; shot segmentation; video mining; video sequences; Data mining; Data preprocessing; Educational institutions; Information systems; Intelligent systems; Internet; Mathematics; Probability; Rough sets; Video compression; Rough Sets; compressed domain; data mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
Conference_Location
Xiamen
Print_ISBN
978-0-7695-3571-5
Type
conf
DOI
10.1109/GCIS.2009.150
Filename
5209378
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