Noise Filtering of New Motion Capture Markers Using Modified K-Means

  • J. C. Barca
  • G. Rumantir
  • R. Li
Part of the Studies in Computational Intelligence book series (SCI, volume 96)

In this report a detailed description of a new set of multicolor Illuminated Contour-Based Markers, to be used for optical motion capture and a modified K-means algorithm, that can be used for filtering out noise in motion capture data are presented. The new markers provide solutions to central problems with current standard spherical flashing LED based markers. The modified K-means algorithm that can be used for removing noise in optical motion capture data, is guided by constraints on the compactness and number of data points per cluster. Experiments on the presented algorithm and findings in literature indicate that this noise removing algorithm outperforms standard filtering algorithms such as Mean and Median because it is capable of completely removing noise with both Spike and Gaussian characteristics. The cleaned motion data can be used for accurate reconstruction of captured movements, which in turn can be compared to ideal models such that ways of improving physical performance can be identified.

Keywords

Color Space Median Filter Motion Capture Motion Capture System Noise Filter 
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 2008

Authors and Affiliations

  • J. C. Barca
    • 1
  • G. Rumantir
    • 1
  • R. Li
    • 1
  1. 1.Department of Information TechnologyMonash UniversityMelbourneAustralia

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