Video based human animation technique
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Tracking People with Twists and Exponential Maps
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Model-based tracking of self-occluding articulated objects
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Towards Real-Time Monocular Video-Based Avatar Animation
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
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In this paper, we present a robust algorithm to capture rapid human motion with self-occlusion. Instead of predicting the position of each human feature, the interest-region of full body is estimated. Then candidate features are extracted through the overall search in the interest-region. To establish the correspondence between candidate features and actual features, an adaptive Bayes classifier is constructed based on the time-varied models of feature attributions. At last, a hierarchical human feature model is adopted to verify and accomplish the feature correspondence. To improve the efficiency, we propose a multiresolution search strategy: the initial candidate feature set is estimated at the low resolution image and successively refined at higher resolution levels. The experiment demonstrates the effectiveness of our algorithm.