A Markerless Motion Capture System to Study Musculoskeletal Biomechanics: Visual Hull and Simulated Annealing Approach.
From: Department of Mechanical Engineering, Stanford University, 496 Lomita Mall, Durand B. 201, CA 94305-4038, USA. stefano.corazza@stanford.edu
Annals of biomedical engineering
- Publish Date: Jun 2006
- ISSN: 0090-6964
- Volume: 34
- Issue: 6
- Pages: 1019-29
- Medium: Print
- Language: English
- Citation (JAMA): Corazza S, Mündermann L, Chaudhari A M, et al. A Markerless Motion Capture System to Study Musculoskeletal Biomechanics: Visual Hull and Simulated Annealing Approach.. Jun 2006;34:1019-29
Abstract
Human motion capture is frequently used to study musculoskeletal biomechanics and clinical problems, as well as to provide realistic animation for the entertainment industry. The most popular technique for human motion capture uses markers placed on the skin, despite some important drawbacks including the impediment to the motion by the presence of skin markers and relative movement between the skin where the markers are placed and the underlying bone. The latter makes it difficult to estimate the motion of the underlying bone, which is the variable of interest for biomechanical and clinical applications. A model-based markerless motion capture system is presented in this study, which does not require the placement of any markers on the subject’s body. The described method is based on visual hull reconstruction and an a priori model of the subject. A custom version of adapted fast simulated annealing has been developed to match the model to the visual hull. The tracking capability and a quantitative validation of the method were evaluated in a virtual environment for a complete gait cycle. The obtained mean errors, for an entire gait cycle, for knee and hip flexion are respectively 1.5 degrees (+/-3.9 degrees ) and 2.0 degrees (+/-3.0 degrees ), while for knee and hip adduction they are respectively 2.0 degrees (+/-2.3 degrees ) and 1.1 degrees (+/-1.7 degrees ). Results for the ankle and shoulder joints are also presented. Experimental results captured in a gait laboratory with a real subject are also shown to demonstrate the effectiveness and potential of the presented method in a clinical environment.
Mesh Headings (Keywords): Biomechanics, Computer Simulation, Humans, Image Interpretation, Computer-Assisted, Joints, Models, Biological, Musculoskeletal Physiology, Photography, Running, Video Recording
Check for Full Text / PubMed Unique Identifier (PMID): 16783657
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