Real-Time Multi-view Human Motion Tracking Using Particle Swarm Optimization with Resampling

  • Bogdan Kwolek
  • Tomasz Krzeszowski
  • André Gagalowicz
  • Konrad Wojciechowski
  • Henryk Josinski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7378)

Abstract

In this paper we propose a particle swarm optimization with resampling for marker-less body tracking. The resampling is employed to select a record of the best particles according to the weights of particles making up the swarm. The algorithm better copes with noise and reduces the premature stagnation. Experiments on 4-camera datasets show the robustness and accuracy of our method. It was evaluated on nine sequences using ground truth provided by Vicon. The full body motion tracking was conducted in real-time on two PC nodes, each of them with two multi-core CPUs with hyper-threading, connected by 1 GigE.

Keywords

Particle Swarm Optimization Human Motion Motion Capture Good Particle Body Tracking 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Bogdan Kwolek
    • 3
    • 2
  • Tomasz Krzeszowski
    • 3
    • 2
  • André Gagalowicz
    • 1
  • Konrad Wojciechowski
    • 2
  • Henryk Josinski
    • 2
  1. 1.INRIA Paris-RocquencourtRocquencourtFrance
  2. 2.Polish-Japanese Institute of Information TechnologyWarszawaPoland
  3. 3.Rzeszów University of TechnologyRzeszówPoland

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