Scene segmentation based on IPCA for visual surveillance

Authors:
Yuan Yuan;Yanwei Pang;Jing Pan;Xuelong Li
Affiliations:
School of Engineering and Applied Science, Aston University, Birmingham B4 7ET, UK;School of Electronic Information Engineering, Tianjin University, Tianjin 300072, China;Electronic Engineering Department, Tianjin University of Technology and Education, Tianjin 300222, China;School of Computer Science and Information Systems, Birkbeck College, University of London, London WC1E 7HX, UK
Venue:
Neurocomputing
Year:
2009

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Abstract

This paper proposes a simple scene segmentation method based on incremental principal component analysis (IPCA). Instead of segmenting moving objects in a conventional frame by frame manner, the newly proposed method segments a scene into unchanged background zone (UBZ) and moving object zone (MOZ). As a result, moving objects normally appear in MOZs rather than UBZs, and therefore, detection and behaviours analysis can be performed in MOZs. In visual communication, UBZs do not need to be encoded and transmitted. Moreover, if an object is in UBZs, it can be linked to abnormal events. Experimental results demonstrate the contribution of the proposed method.