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2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '03) - Volume 2
Markerless Kinematic Model and Motion Capture from Volume Sequences
Madison, Wisconsin
June 18-June 20
ISBN: 0-7695-1900-8
Chi-Wei Chu, University of Southern California
Odest Chadwicke Jenkins, University of Southern California
Maja J Mataric, University of Southern California
We present an approach for model-free markerless motion capture of articulated kinematic structures. This approach is centered on our method for generating underlying nonlinear axes (or a skeleton curve) of a volume of genus zero (i.e., without holes). We describe the use of skeleton curves for deriving a kinematic model and motion (in the form of joint angles over time) from a captured volume sequence. Our motion capture method uses a skeleton curve, found in each frame of a volume sequence, to automatically determine kinematic postures. These postures are aligned to determine a common kinematic model for the volume sequence. The derived kinematic model is then reapplied to each frame in the volume sequence to find the motion sequence suited to this model. We demonstrate our method on several types of motion, from synthetically generated volume sequences with an arbitrary kinematic topology, to human volume sequences captured from a set of multiple calibrated cameras.
Citation:
Chi-Wei Chu, Odest Chadwicke Jenkins, Maja J Mataric, "Markerless Kinematic Model and Motion Capture from Volume Sequences," cvpr, vol. 2, pp.475, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '03) - Volume 2, 2003
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