Object extraction in video sequences based on spatiotemporal independent component analysis

被引:0
|
作者
Chen, ZH [1 ]
Zhang, XP [1 ]
机构
[1] Ryerson Univ, Dept Elect & Comp Engn, Toronto, ON M5B 2K3, Canada
关键词
content-based video retrieval (CBVR); independent component analysis (ICA); spatiotemporal independent component analysis (stICA); wavelets; object segmentation; multiscale analysis;
D O I
10.1117/12.503167
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Compression and content-based video retrieval (CBVR) are essential needs for efficient and intelligent utilizations of vast multimedia databases over the Internet. In video sequences, object based extraction techniques are gaining importance in achieving compression and performing content-based video retrieval. In this paper, a novel technique is developed to extract objects from video sequences based on spatiotemporal independent component analysis (stICA) and multiscale analysis. The stICA is used to extract the preliminary source images containing moving objects in the video sequences. The source image data obtained after stICA analysis are further processed using wavelet based multiscale image segmentation and region detection techniques to improve the accuracy of the extracted object. Preliminary results demonstrate great potential for stICA based object extraction technique in content-based video processing applications.
引用
收藏
页码:358 / 365
页数:8
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