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Real-Time Multi-view Human Motion Tracking Using 3D Model and Latency Tolerant Parallel Particle Swarm Optimization

  • Bogdan Kwolek
  • Tomasz Krzeszowski
  • Konrad Wojciechowski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6930)

Abstract

This paper demonstrates how latency tolerant parallel particle swarm optimization can be used to achieve real-time full-body motion tracking. The tracking is realized using multi-view images and articulated 3D model with a truncated cones-based representation of the body. Each CPU core computes fitness score for a single camera. On each node the algorithm uses the current temporary best fitness value without waiting for the global best one from cooperating sub-swarms. The algorithm runs at 10 Hz on eight PC nodes connected by 1 GigE.

Keywords

Motion Capture Object Tracking Motion Tracking Motion Capture Data Master Thread 
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 2011

Authors and Affiliations

  • Bogdan Kwolek
    • 1
    • 2
  • Tomasz Krzeszowski
    • 2
    • 1
  • Konrad Wojciechowski
    • 2
  1. 1.Rzeszów University of TechnologyRzeszówPoland
  2. 2.Polish-Japanese Institute of Information TechnologyWarszawaPoland

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