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EURASIP Journal on Advances in Signal Processing
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Using Gaussian Process Annealing Particle Filter for 3D Human Tracking

EURASIP Journal on Advances in Signal Processing volume 2008, Article number: 592081 (2007) Cite this article

Abstract

We present an approach for human body parts tracking in 3D with prelearned motion models using multiple cameras. Gaussian process annealing particle filter is proposed for tracking in order to reduce the dimensionality of the problem and to increase the tracker's stability and robustness. Comparing with a regular annealed particle filter-based tracker, we show that our algorithm can track better for low frame rate videos. We also show that our algorithm is capable of recovering after a temporal target loss.

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Authors and Affiliations

  1. Computer Science Department, Technion - Israel Institute of Technology, Technion City, Haifa, 32000, Israel

    Leonid Raskin, Ehud Rivlin & Michael Rudzsky

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  1. Leonid Raskin
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  2. Ehud Rivlin
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  3. Michael Rudzsky
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Correspondence to Leonid Raskin.

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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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Raskin, L., Rivlin, E. & Rudzsky, M. Using Gaussian Process Annealing Particle Filter for 3D Human Tracking. EURASIP J. Adv. Signal Process. 2008, 592081 (2007). https://doi.org/10.1155/2008/592081

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  • DOI: https://doi.org/10.1155/2008/592081

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