Completely automated end-to-end method and system for markerless motion capture performs segmentation of articulating objects in Laplacian Eigenspace and is applicable to handling of the poses of some complexity. 3D voxel representation of acquired images are mapped to a higher dimensional space (k), where k depends on the number of articulated chains of the subject body, so as to extract the 1-D representations of the articulating chains. A bottom-up approach is suggested in order to build a parametric (spline-based) representation of a general articulated body in the high dimensional space followed by a top-down probabilistic approach that registers the segments to an average human body model. The parameters of the model are further optimized using the segmented and registered voxels.
Method and system for markerless motion capture using multiple cameras