Articulated Body Motion Tracking by Combined Particle Swarm Optimization and Particle Filtering

This paper proposes the use of a particle filter with embedded particle swarm optimization as an efficient and effective way of dealing with 3d model-based human body tracking. A particle swarm optimization algorithm is utilized in the particle filter to shift the particles toward more promising configurations of the human model. The algorithm is shown to be able of tracking full articulated body motion efficiently. It outperforms the annealed particle filter, kernel particle filter as well as a tracker based on particle swarm optimization. Experiments on real video sequences as well as a qualitative analysis demonstrate the strength of the approach.