Monocular 3D tracking of articulated human motion in silhouette and pose manifolds
Journal on Image and Video Processing - Anthropocentric Video Analysis: Tools and Applications
View-Invariant Human Action Recognition Using Exemplar-Based Hidden Markov Models
ICIRA '09 Proceedings of the 2nd International Conference on Intelligent Robotics and Applications
Coupled Visual and Kinematic Manifold Models for Tracking
International Journal of Computer Vision
Exploiting spatio-temporal constraints for robust 2D pose tracking
Proceedings of the 2nd conference on Human motion: understanding, modeling, capture and animation
Advances in view-invariant human motion analysis: a review
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Dual gait generative models for human motion estimation from a single camera
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
Manifold topological multi-resolution analysis method
Pattern Recognition
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Inferring 3D body pose as well as viewpoint from a single silhouette image is a challenging problem. We present a new generative model to represent shape deformations according to view and body configuration changes on a two dimensional manifold. We model the two continuous states by a product space (different configurations 脳 different views) embedded on a conceptual two dimensional torus manifold. We learn a nonlinear mapping between torus manifold embedding and visual input (silhouettes) using empirical kernel mapping. Since every view and body pose has a corresponding embedding point on the torus manifold, inferring view and body pose from a given image becomes estimating the embedding point from a given input. As the shape varies in different people even in the same view and body pose, we extend our model to be adaptive to different people by decomposing person dependent style factors. Experimental results with real data as well as synthetic data show simultaneous estimation of view and body configuration from given silhouettes from unknown people.