Abstract
Video content analysis is essential for efficient and intelligent utilizations of vast multimedia databases over the Internet. In video sequences, object-based extraction techniques are important for content-based video processing in many applications. 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 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. An automated video object extraction system is developed based on these new techniques. Preliminary results demonstrate great potential for the new stICA and multiscale-segmentation-based object extraction system in content-based video processing applications.
Highlights
The increasing popularity of video processing is due to the high demand for video in entertainment, security related applications, education, telemedicine, database, and new wireless telecommunications
The main contributions of this paper include: (i) a new method to analyze video sequences based on the spatiotemporal independent component analysis (stICA) model; (ii) a novel compensation method to deal with the nonlinear combination problem in the stICA model for video sequences; (iii) the integrated postprocessing techniques based on wavelet analysis, edge detection with region growing, and multiscale segmentation approaches
A new automated video object extraction system is presented based on the stICA and multiscale analysis
Summary
The increasing popularity of video processing is due to the high demand for video in entertainment, security related applications, education, telemedicine, database, and new wireless telecommunications. Kim and Hwang [8] utilized edge change information to extract video objects Another spatiotemporal segmentation approach based on edge flow and 3D motion estimation was proposed in [9]. The main contributions of this paper include: (i) a new method to analyze video sequences based on the stICA model; (ii) a novel compensation method to deal with the nonlinear combination problem in the stICA model for video sequences; (iii) the integrated postprocessing techniques based on wavelet analysis, edge detection with region growing, and multiscale segmentation approaches. FRAMEWORK OF A NEW AUTOMATED VIDEO OBJECT EXTRACTION SYSTEM USING ICA AND MULTISCALE ANALYSIS
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