DocumentCode
483223
Title
A Novel RS-based Key Frame Representation for Video Mining in Compressed-Domain
Author
Li Xiang-wei ; Zhang Ming-xin ; Zhu Ya-lin ; Xin jin-hong
Author_Institution
Dept. of Comput. Eng., Lanzhou Polytech. Coll., Lanzhou
fYear
2009
fDate
23-25 Jan. 2009
Firstpage
199
Lastpage
201
Abstract
It is a challenging issue to analyze video content for video mining tasks due to lacking of effective representation of video. In this paper, we propose a novel key frame representation algorithm based on rough sets (RS) in discrete cosine transform (DCT) compressed-domain. Firstly, we extract DCT coefficients in compressed-domain, select and preprocess the DC coefficients that derived from DCT coefficients. Secondly, we construct information system with DC coefficients. Finally, we reduce information system using attributes reduced theory of RS, and obtained the representation of the video frames by reduced DC coefficients. Experimental results show that the proposed algorithm is fast and effective. Compared to conventional algorithm, our algorithm enjoys the following advantages: (1) the numbers of the key frame extracted using our algorithm become more scientific; (2) the algorithm can avoid the expensive computations in decompression processes.
Keywords
data compression; data mining; data reduction; discrete cosine transforms; image representation; rough set theory; video coding; DCT coefficient extraction; attribute reduction theory; discrete cosine transform compressed-domain; information system; rough set-based video key frame representation; video content analysis; video decompression process; video mining; video representation; Data engineering; Data mining; Discrete cosine transforms; Educational institutions; Indexing; Information analysis; Information systems; Knowledge engineering; Rough sets; Video compression; Compressed Domain; Key Frame; Rough Sets;
fLanguage
English
Publisher
ieee
Conference_Titel
Knowledge Discovery and Data Mining, 2009. WKDD 2009. Second International Workshop on
Conference_Location
Moscow
Print_ISBN
978-0-7695-3543-2
Type
conf
DOI
10.1109/WKDD.2009.84
Filename
4771912
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