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Selective eigenbackgrounds method for background subtraction in crowed scenes

  • Zhipeng Hu
  • , Yaowei Wang*
  • , Yonghong Tian
  • , Tiejun Huang
  • *Corresponding author for this work
  • Chinese Academy of Sciences
  • Peking University
  • Beijing Institute of Technology

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

Abstract

In this paper, a selective eigenbackgrounds method is proposed for background subtraction in crowded scenes. In order to train and update the eigenbackground model with frames containing few objects (i.e. clean frames), virtual frames are constructed based on a frame selection map. Then, the eigenbackground that best depicts background is selected for each pixel based on an eigenbackground selection map. Experimental results show the performance of the proposed method is better than those of some state-of-the-art methods in crowded scenes.

Original languageEnglish
Title of host publicationICIP 2011
Subtitle of host publication2011 18th IEEE International Conference on Image Processing
Pages3277-3280
Number of pages4
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: 11 Sep 201114 Sep 2011

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2011 18th IEEE International Conference on Image Processing, ICIP 2011
Country/TerritoryBelgium
CityBrussels
Period11/09/1114/09/11

Keywords

  • background subtraction
  • crowded scenes
  • eigenbackground
  • video surveillance

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