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Scene segmentation based on seeded region growing for foreground detection

  • Hongwu Qin
  • , Jasni Mohamad Zain
  • , Xiuqin Ma
  • , Tao Hai
  • Universiti Malaysia Pahang Al-Sultan Abdullah

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

6 Scopus citations

Abstract

This paper proposes a scene segmentation method for foreground detection in outdoor visual surveillance. An outdoor scene is divided into three parts: road, sky, and other region by using seeded region growing (SRG) algorithm in which road region gets initial seeds by using the motion information of vehicles and sky region gets initial seeds by using a probabilistic classifier. As a result, instead of detecting foreground objects in a conventional pixel by pixel manner, detection can be performed selectively on the pixels of partial regions in terms of different surveillant requirement so as to facilitate and accelerate foreground detection. Experimental results show the contribution of our proposed method.

Original languageEnglish
Title of host publicationProceedings - 2010 6th International Conference on Natural Computation, ICNC 2010
Pages3619-3623
Number of pages5
DOIs
StatePublished - 2010
Externally publishedYes
Event2010 6th International Conference on Natural Computation, ICNC'10 - Yantai, Shandong, China
Duration: 10 Aug 201012 Aug 2010

Publication series

NameProceedings - 2010 6th International Conference on Natural Computation, ICNC 2010
Volume7

Conference

Conference2010 6th International Conference on Natural Computation, ICNC'10
Country/TerritoryChina
CityYantai, Shandong
Period10/08/1012/08/10

Keywords

  • Foreground detection
  • Scene segmentation
  • Seeded region growing
  • Visual surveillance

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