Scene segmentation based on IPCA for visual surveillance

Yuan Yuan*, Yanwei Pang, Jing Pan, Xuelong Li

*Corresponding author for this work

Research output: Contribution to journalArticle

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.

Original languageEnglish
Pages (from-to)2450-2454
Number of pages5
JournalNeurocomputing
Volume72
Issue number10-12
Early online date3 Dec 2008
DOIs
Publication statusPublished - Jun 2009

Keywords

  • incremental principal component analysis
  • scene segmentation
  • video surveillance
  • visual surveillance

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