Video Tracking Using Dual-Tree Wavelet Polar Matching and Rao-Blackwellised Particle Filter

  • Sze Kim Pang
  • James D.B. Nelson
  • Simon J. Godsill
  • Nick Kingsbury
Open Access
Research Article
  • 1k Downloads

Abstract

We describe a video tracking application using the dual-tree Polar Matching Algorithm. We develop the dynamical and observation models in a probabilistic setting and study the empirical probability distribution of the Polar Matching output. We model the visible and occluded target statistics using Beta distributions. This is incorporated into a Track-Before-Detect (TBD) solution for the overall observation likelihood of each video frame and provides a principled derivation of the observation likelihood. Due to the nonlinear nature of the problem, we design a Rao-Blackwellised Particle Filter (RBPF) for the sequential inference. Computer simulations demonstrate the ability of the algorithm to track a simulated video moving target in an urban environment with complete and partial occlusions.

Keywords

Probabilistic Setting Video Frame Beta Distribution Observation Model Partial Occlusion 

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Copyright information

© Sze Kim Pang et al. 2009

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Authors and Affiliations

  • Sze Kim Pang
    • 1
  • James D.B. Nelson
    • 1
  • Simon J. Godsill
    • 1
  • Nick Kingsbury
    • 1
  1. 1.Signal Processing and Communications Laboratory, Engineering DepartmentCambridge UniversityCambridgeUK

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