Motion-based background modeling for moving object detection on moving platforms

Ming Yu Shih*, Yao Jen Chang, Bwo Chau Fu, Ching-Chun Huang

*Corresponding author for this work

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

21 Scopus citations

Abstract

A method to detect moving objects on non-stationary background is proposed. The concurrent motions of foreground and background pixels make it extremely difficult to maintain a plausible background model for background subtraction. In our method, motion fields of aligned neighboring frames are fused to reduce parallax effects in moving blob detection. A fused color background model is further developed to refine shapes of detected objects. Finally, moving blob information is incorporated into the adaptation process of background model. Only confidently marked background pixels are adapted into background models with each incoming frame. Experimental results shown robust, well-shaped moving object detection can be obtained under unconstrained scenes.

Original languageEnglish
Title of host publicationProceedings of 16th International Conference on Computer Communications and Networks 2007, ICCCN 2007
Pages1178-1182
Number of pages5
DOIs
StatePublished - 1 Dec 2007
Event16th International Conference on Computer Communications and Networks 2007, ICCCN 2007 - Honolulu, HI, United States
Duration: 13 Aug 200716 Aug 2007

Publication series

NameProceedings - International Conference on Computer Communications and Networks, ICCCN
ISSN (Print)1095-2055

Conference

Conference16th International Conference on Computer Communications and Networks 2007, ICCCN 2007
Country/TerritoryUnited States
CityHonolulu, HI,
Period13/08/0716/08/07

Keywords

  • Background modeling
  • Object detection
  • Optical flow

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