A colour statistical approach to phantom pruning in multi-view detection

Jie Ren, Ming Xu, Jeremy S. Smith

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

Abstract

To increase the robustness of detection in intelligent video surveillance systems, homography has been widely used to fuse foreground regions projected from multiple camera views to a reference view. However, the intersections of non-corresponding foreground regions can cause phantoms. This paper proposes a colour statistical approach to cope with this problem. This method is based on the Mahalanobis distance between the colour patches which correspond to the same foreground region in the reference view. This method can overcome the problems in the pixelwise colour correlation approach.

Original languageEnglish
Title of host publicationProceedings 2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012
Pages756-761
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012 - Seoul, Korea, Republic of
Duration: 14 Oct 201217 Oct 2012

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)1062-922X

Conference

Conference2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012
Country/TerritoryKorea, Republic of
CitySeoul
Period14/10/1217/10/12

Keywords

  • homography
  • motion detection
  • video surveillance

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