Multicue HMM-UKF for real-time contour tracking

Yunqiang Chen, Yong Rui, Thomas S. Huang

Research output: Contribution to journalArticlepeer-review

Abstract

We propose an HMM model for contour detection based on multiple visual cues in spatial domain and improve it by joint probabilistic matching to reduce background clutter. It is further integrated with unscented Kalman filter to exploit object dynamics in nonlinear systems for robust contour tracking.

Original languageEnglish (US)
Pages (from-to)1525-1529
Number of pages5
JournalIEEE transactions on pattern analysis and machine intelligence
Volume28
Issue number9
DOIs
StatePublished - Sep 1 2006

Keywords

  • HMM
  • Joint probabilistic matching
  • Parametric contour
  • Unscented Kalman filters

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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