Scene segmentation based on IPCA for visual surveillance

Yuan, Y. and Pang, Y. and Pan, J. and Li, Xuelong (2009) Scene segmentation based on IPCA for visual surveillance. Neurocomputing 72 (10-12), pp. 2450-2455. ISSN 0925-2312.

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Official URL: http://dx.doi.org/10.1016/j.neucom.2008.11.013

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.

Metadata

Item Type:	Article
Keyword(s) / Subject(s):	Incremental principal component analysis, visual surveillance, video surveillance, scene segmentation
School:	Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
Depositing User:	Administrator
Date Deposited:	07 Feb 2011 12:04
Last Modified:	09 Aug 2023 12:30
URI:	https://eprints.bbk.ac.uk/id/eprint/1867

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