Open Access

Using Gaussian Process Annealing Particle Filter for 3D Human Tracking

EURASIP Journal on Advances in Signal Processing20072008:592081

Received: 31 January 2007

Accepted: 16 September 2007

Published: 22 November 2007


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’ Affiliations

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


© Leonid Raskin et al. 2008

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.