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Estimation of hurdle clearance parameters using a monocular human motion tracking method

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  • Tomasz Krzeszowski
  • Krzysztof Przednowek
  • Krzysztof Wiktorowicz
  • Janusz Iskra

Abstract

This paper presents a method of monocular human motion tracking for estimation of hurdle clearance kinematic parameters. The analysis involved 10 image sequences of five hurdlers at various training levels. Recording of the sequences was carried out under simulated starting conditions of a 110 m hurdle race. The parameters were estimated using the particle swarm optimization algorithm and they are based on analysis of the images recorded with a 100 Hz camera. The proposed method does not involve using any special clothes, markers, inertial sensors, etc. As the quality criteria, the mean absolute error and mean relative error were used. The level of computed errors justifies the use of this method to estimate hurdle clearance parameters.

Suggested Citation

  • Tomasz Krzeszowski & Krzysztof Przednowek & Krzysztof Wiktorowicz & Janusz Iskra, 2016. "Estimation of hurdle clearance parameters using a monocular human motion tracking method," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 19(12), pages 1319-1329, September.
    • Handle: RePEc:taf:gcmbxx:v:19:y:2016:i:12:p:1319-1329
    DOI: 10.1080/10255842.2016.1139092
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    References listed on IDEAS

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    1. Ricardo M.L. Barros & Rafael P. Menezes & Tiago G. Russomanno & Milton S. Misuta & Bruno C. Brandão & Pascual J. Figueroa & Neucimar J. Leite & Siome K. Goldenstein, 2011. "Measuring handball players trajectories using an automatically trained boosting algorithm," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 14(01), pages 53-63.
    2. Sanjay Saini & Nordin Zakaria & Dayang Rohaya Awang Rambli & Suziah Sulaiman, 2015. "Markerless Human Motion Tracking Using Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-22, May.
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