Evaluating Video-Based Motion Capture
CA '02 Proceedings of the Computer Animation
Tracking People with Twists and Exponential Maps
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Monocular 3-D Tracking of the Golf Swing
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Human motion reconstruction from monocular images using genetic algorithms: Research Articles
Computer Animation and Virtual Worlds - Special Issue: The Very Best Papers from CASA 2004
Performance animation from low-dimensional control signals
ACM SIGGRAPH 2005 Papers
Recovering 3D Human Pose from Monocular Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning silhouette features for control of human motion
SIGGRAPH '04 ACM SIGGRAPH 2004 Sketches
Markerless monocular motion capture using image features and physical constraints
CGI '05 Proceedings of the Computer Graphics International 2005
Inferring 3D body pose from silhouettes using activity manifold learning
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
3D Human Motion Reconstruction Using Video Processing
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
A script engine for realistic human motion generation
International Journal of Computer Applications in Technology
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A robust, adaptive system for reconstructing 3D human motion from monocular video is presented. Our system takes a model based approach. To save computation time, we fit the skeleton instead of full body model to the silhouette. End sites positions identified from the silhouettes serve as an extra constraint. The alleviation of computational burden then makes the use of simulated annealing practical to get rid of local minima. The identifiable end sites also serve as the criterion to judge the reconstruction reliability of single frames. According to different reliabilities, the video is segmented into sections, which are reconstructed using different strategies. Our system is robust, getting rid of error accumulation in tracking, and adaptive, being able to tell the user when and where more information is needed.