Object tracking with probabilistic hausdorff distance matching

Sang Cheol Park, Seong Whan Lee

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

This paper proposes a new method of extracting and tracking a nonrigid object moving while allowing camera movement. For object extraction we first detect an object using watershed segmentation technique and then extract its contour points by approximating the boundary using the idea of feature point weighting. For object tracking we take the contour to estimate its motion in the next frame by the maximum likelihood method. The position of the object is estimated using a probabilistic Hausdorff measurement while the shape variation is modelled using a modified active contour model. The proposed method is highly tolerant to occlusion. Because the tracking result is stable unless an object is fully occluded during tracking, the proposed method can be applied to various applications.

Original languageEnglish
Pages (from-to)233-242
Number of pages10
JournalLecture Notes in Computer Science
Volume3644
Issue numberPART I
DOIs
Publication statusPublished - 2005
EventInternational Conference on Intelligent Computing, ICIC 2005 - Hefei, China
Duration: 2005 Aug 232005 Aug 26

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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