Group-Valued regularization framework for motion segmentation of dynamic non-rigid shapes
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
SMI 2012: Full α-Decomposition of polygons
Computers and Graphics
Motion-based mesh segmentation using augmented silhouettes
Graphical Models
Articulated motion segmentation of point clouds by group-valued regularization
EG 3DOR'12 Proceedings of the 5th Eurographics conference on 3D Object Retrieval
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We present a novel approach to solve the problem of segmenting a sequence of animated objects into near-rigid components based on k given poses of the same non-rigid object. We model the segmentation problem as a clustering problem in dual space and find near-rigid segments with the property that segment boundaries are located at regions of large deformation. The presented approach is asymptotically faster than previous approaches that achieve the same property and does not require any user-specified parameters. However, if desired, the user may interactively change the number of segments. We demonstrate the practical value of our approach using experiments.