Using Gaussian Process Annealing Particle Filter for 3D Human Tracking
© Leonid Raskin et al. 2008
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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