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
Link To Document :
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