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
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;
Conference_Titel :
Internet Technology and Applications (iTAP), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7253-6
DOI :
10.1109/ITAP.2011.6006321
