Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Estimating 3-D rigid body transformations: a comparison of four major algorithms
Machine Vision and Applications - Special issue on performance evaluation
A Mathematical Introduction to Robotic Manipulation
A Mathematical Introduction to Robotic Manipulation
Human Body Model Acquisition and Tracking Using Voxel Data
International Journal of Computer Vision
Tracking People with Twists and Exponential Maps
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Articulated Soft Objects for Multiview Shape and Motion Capture
IEEE Transactions on Pattern Analysis and Machine Intelligence
Twist Based Acquisition and Tracking of Animal and Human Kinematics
International Journal of Computer Vision
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Articulated Body Motion Capture by Stochastic Search
International Journal of Computer Vision
SCAPE: shape completion and animation of people
ACM SIGGRAPH 2005 Papers
A Quantitative Evaluation of Video-based 3D Person Tracking
ICCCN '05 Proceedings of the 14th International Conference on Computer Communications and Networks
Automatic rigging and animation of 3D characters
ACM SIGGRAPH 2007 papers
Articulated mesh animation from multi-view silhouettes
ACM SIGGRAPH 2008 papers
ACM SIGGRAPH 2008 posters
Markerless Motion Capture through Visual Hull, Articulated ICP and Subject Specific Model Generation
International Journal of Computer Vision
Optimization and Filtering for Human Motion Capture
International Journal of Computer Vision
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We propose a human motion tracking method that not only captures the motion of the skeleton model but also generates a sequence of surfaces using images acquired by multiple synchronized cameras. Our method extracts articulated postures with 42 degrees of freedom through a sequence of visual hulls. We seek a globally optimized solution for likelihood using local memorization of the ''fitness'' of each body segment. Our method efficiently avoids problems of local minima by using a mean combination and an articulated combination of particles selected according to the weights of the different body segments. The surface is produced by deforming the template and the details are recovered by fitting the deformed surface to 2D silhouette rims. The extracted posture and estimated surface are cooperatively refined by registering the corresponding body segments. In our experiments, the mean error between the samples of the deformed reference model and the target is about 2cm and the mean matching difference between the images projected by the estimated surfaces and the original images is about 6%.