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A Comparison of Feature Measurements for Kinetic Studies on Human Bodies

  • Nikki Austin
  • Yen Chen
  • Reinhard Klette
  • Robert Marshall
  • Yuan-sheng Tsai
  • Yongbao Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1998)

Abstract

The paper reports about a performance comparison within a joint project of omputer vision, and sport and exercise sciences. The project is directed on the understanding of human motion based on shape features and kinetic studies. Three shape recovery techniques, a traditional technique as used in sport and exercise sciences (manual measurement based on an elliptical zone assumption) and two omputer vision techniques (based on a small number of of luding ontours, and a new ombination of photometri stereo and shape from boundaries), are ompared using a mannequin as test object. The omputer vision techniques have been designed to go towards dynamic shape recovery (humans in motion). The paper reports about these three techniques and their measurement accuracies.

Keywords

Shape Recovery Elliptical Cylinder Contour Method Photometric Stereo Exercise Science 
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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References

  1. 1.
    N. Austin: Estimation of segmental inertial parameter variation in hildren: Implication for gait analysis. Master thesis, Sport and Exercise Sciences, The University of Au kland (2000).Google Scholar
  2. 2.
    R.F. Chandler, C.E. Clauster, J.T. McConville, H.M. Reynolds, J.W. Young: Investigation of inertial properties of the human body. AMRL Technical Report, TR–74–137 (1975). 43Google Scholar
  3. 3.
    C.E. Clauster, J.T. McConville, J.W. Young: Weight,volume and enter of mass of segments of the human body. AMRL Technical Report, TR–69–70 (1969). 43Google Scholar
  4. 5.
    W.D. Dempster: Space requirements of the seated operator.WADC Te hnical Report 55–159 (1955).Google Scholar
  5. 6.
    R. Frankot, R. Chellappa: Amethod for enforcing integrability in shape from shading algorithms. IEEE Trans. on Pattern Analysis and Machine Intelligence PAMI-10 (1988) 439–451.47CrossRefGoogle Scholar
  6. 7.
    R.K. Jensen: Estimation of the biome hani al properties of three body types using a photogrammetric method. J. of Biomechanics 11 (1978) 349–358. 45, 46CrossRefGoogle Scholar
  7. 8.
    R. Klette, K.Shlüns, Height data from gradient fields Proc.SPIE, 2908, pp.204–215, 1996.47CrossRefGoogle Scholar
  8. 9.
    R. Klette, K.S hlüns, A. Koschan: Computer Vision: Three-dimensional Data from Images Springer, Singapore (1998).Google Scholar
  9. 10.
    J.J. Koenderink: Solid Shape Cambridge, MA, MIT Press (1990). 47Google Scholar
  10. 11.
    R.N. Marshall, R.K. Jensen, G.A. Wood: A general Newtonian simulation of an n-segment open hain model. J. of Biomechanics 18 (1985) 359–368. 43CrossRefGoogle Scholar
  11. 12.
    B.M. Nigg, W. Herzog: Biomechanics of the Musculo-Skeletal System Wiley, New York (1994). 44Google Scholar
  12. 14.
    S. Tokai, T. Wada, T. Matsuyama: Real time 3D shape re onstruction using PC cluster system. Pro. 3rd Internat. Workshop Cooperative Distributed Vision Kyoto (1999) 171–187. 45Google Scholar
  13. 15.
    R.Y. Tsai: An efficient and accurate camera calibration te hnique for 3D ma hine vision. Proc. Internat. Conf. Computer Vision and Pattern Recognition (1986) 364–374. 47Google Scholar
  14. 17.
    R.J. Woodham: Photometric method for determining surface orientation from multiple images.Optical Engineering 19 (1980) 139–144.47Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Nikki Austin
    • 2
  • Yen Chen
    • 1
  • Reinhard Klette
    • 1
  • Robert Marshall
    • 2
  • Yuan-sheng Tsai
    • 1
  • Yongbao Zhang
    • 1
  1. 1.Center for Image Technology and RoboticsUSA
  2. 2.Department of Sport and Exer ise SciencesThe University of AucklandAucklandNew Zealand

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