DocumentCode
3106584
Title
Video Analysis Based on FSVM with Fuzzy Clustering
Author
Jie, Chen ; Ya-hui Ma
Author_Institution
Comput. Sch., Hubei Univ. of Technol., Wuhan, China
fYear
2011
fDate
16-18 Aug. 2011
Firstpage
1
Lastpage
3
Abstract
The voluminous data analysis is an obstacle for video indexing and retrieval, a novel method based on video frame difference is proposed to make the fast indexing: firstly frame clustering with FSVM is used to extract the important scene in video; secondly the scenes are labelled with characteristic features; finally, the associated rule data-mining is used to fabricate the last video analysis. The experimental results suggest that the proposed method is an effective approach for video analysis.
Keywords
data mining; fuzzy set theory; image colour analysis; indexing; pattern clustering; support vector machines; video retrieval; video signal processing; FSVM; associated rule data-mining; color distance histogram; frame clustering; fuzzy clustering; important scene extraction; video analysis; video frame difference; video indexing; video retrieval; voluminous data analysis; Clustering algorithms; Color; Feature extraction; Histograms; Streaming media; Support vector machine classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Internet Technology and Applications (iTAP), 2011 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-7253-6
Type
conf
DOI
10.1109/ITAP.2011.6006321
Filename
6006321
Link To Document