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Non-Rigid Modeling of Body Segments for Improved Skeletal Motion Estimation

Eugene J. Alexander1, Christoph Bregler2, Thomas P. Andriacchi3
Div. of Biomechanical Engineering Dept. of Mechanical Engineering Mail Code: 3030Stanford Univeristy, Stanford, CA 94301Ph: 650-723-9317 Fx: 650-725-1587gene.alexander@stanford.edu
Dept. of Computer Science
Dept. of Functional Restoration

Computer Modeling in Engineering & Sciences 2003, 4(3&4), 351-364. https://doi.org/10.3970/cmes.2003.004.351

Abstract

A necessary requirement for many musculoskeletal modeling tasks is an estimation of skeletal motion from observations of the surface of a body segment. The skeletal motion may be used directly for inverse kinematic calculations or as an observation sequence for forward dynamic simulations. This paper describes a fundamentally new approach to human motion capture for biomechanical analysis. Techniques for generating three-dimensional models of human skeletal elements from magnetic resonance imaging data are described, along with a methodology for corresponding these high-resolution internal models to externally observable features. A system for generating dynamic visualizations of these skeletal models from retro-reflective, skin-mounted marker motion capture data is also developed. Next, a set of techniques for estimating body segment shape and pose without the need for retro-reflective markers, from single and multiple, calibrated and un-calibrated cameras is developed. Example results from both synthetic and actual data sequences are presented.

Cite This Article

Alexander, E. J., Bregler, C., Andriacchi, T. P. (2003). Non-Rigid Modeling of Body Segments for Improved Skeletal Motion Estimation. CMES-Computer Modeling in Engineering & Sciences, 4(3&4), 351–364.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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