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

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.

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Correspondence to Sze Kim Pang.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Pang, S.K., Nelson, J.D., Godsill, S.J. et al. Video Tracking Using Dual-Tree Wavelet Polar Matching and Rao-Blackwellised Particle Filter. EURASIP J. Adv. Signal Process. 2009, 620404 (2010). https://doi.org/10.1155/2009/620404

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Keywords

  • Probabilistic Setting
  • Video Frame
  • Beta Distribution
  • Observation Model
  • Partial Occlusion