A complete system for head tracking using motion-based particle filter and randomly perturbed active contour

N. Bouaynaya, D. Schonfeld

Research output: Contribution to journalConference articlepeer-review

19 Scopus citations

Abstract

Many real world applications in computer and multimedia such as augmented reality and environmental imaging require an elastic accurate contour around a tracked object. In the first part of the paper we introduce a novel tracking algorithm that combines a motion estimation technique with the Bayesian Importance Sampling framework. We use Adaptive Block Matching (ABM) as the motion estimation technique. We construct the proposal density from the estimated motion vector. The resulting algorithm requires a small number of particles for efficient tracking. The tracking is adaptive to different categories of motion even with a poor a priori knowledge of the system dynamics. Particulary off-line learning is not needed. A parametric representation of the object is used for tracking purposes. In the second part of the paper, we refine the tracking output from a parametric sample to an elastic contour around the object. We use a 1D active contour model based on a dynamic programming scheme to refine the output of the tracker. To improve the convergence of the active contour, we perform the optimization over a set of randomly perturbed initial conditions. Our experiments are applied to head tracking. We report promising tracking results in complex environments.

Original languageEnglish (US)
Article number97
Pages (from-to)864-873
Number of pages10
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5685
Issue numberPART 2
DOIs
StatePublished - 2005
Externally publishedYes
EventProceedings of SPIE-IS and T Electronic Imaging - Image and Video Communications and Processing 2005 - San Jose, CA, United States
Duration: Jan 18 2005Jan 20 2005

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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