Real-Time tracking of full-body motion using parallel particle swarm optimization with a pool of best particles

Authors:
Tomasz Krzeszowski;Bogdan Kwolek;Boguslaw Rymut;Konrad Wojciechowski;Henryk Josinski
Affiliations:
Rzeszów University of Technology, Rzeszów, Poland and Polish-Japanese Institute of Information Technology, Warszawa, Poland;Rzeszów University of Technology, Rzeszów, Poland and Polish-Japanese Institute of Information Technology, Warszawa, Poland;Rzeszów University of Technology, Rzeszów, Poland and Polish-Japanese Institute of Information Technology, Warszawa, Poland;Polish-Japanese Institute of Information Technology, Warszawa, Poland;Polish-Japanese Institute of Information Technology, Warszawa, Poland
Venue:
SIDE'12 Proceedings of the 2012 international conference on Swarm and Evolutionary Computation
Year:
2012

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Abstract

In this paper we present a particle swarm optimization (PSO) based approach for marker-less full body motion tracking. The objective function is smoothed in an annealing scheme and then quantized. This allows us to extract a pool of candidate best particles. The algorithm selects a global best from such a pool to force the PSO jump out of stagnation. Experiments on 4-camera datasets demonstrate the robustness and accuracy of our method. The tracking is conducted on 2 PC nodes with multi-core CPUs, connected by 1 GigE. This makes our system capable of accurately recovering full body movements with 14 fps.