Hierarchical face clustering on polygonal surfaces
I3D '01 Proceedings of the 2001 symposium on Interactive 3D graphics
Hierarchical mesh decomposition using fuzzy clustering and cuts
ACM SIGGRAPH 2003 Papers
Deformation transfer for triangle meshes
ACM SIGGRAPH 2004 Papers
Variational shape approximation
ACM SIGGRAPH 2004 Papers
ACM SIGGRAPH 2005 Papers
Hierarchical mesh segmentation based on fitting primitives
The Visual Computer: International Journal of Computer Graphics
Segmenting a deforming mesh into near-rigid components
The Visual Computer: International Journal of Computer Graphics
A benchmark for 3D mesh segmentation
ACM SIGGRAPH 2009 papers
Rapid and effective segmentation of 3D models using random walks
Computer Aided Geometric Design
Mesh scissoring with minima rule and part salience
Computer Aided Geometric Design - Special issue: Geometry processing
Segmenting animated objects into near-rigid components
The Visual Computer: International Journal of Computer Graphics
ACM Transactions on Graphics (TOG)
Gaussian-like spatial priors for articulated tracking
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Cascaded models for articulated pose estimation
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Shape Recognition with Spectral Distances
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
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Motion-based segmentation, the problem of detecting rigid parts of an articulated three-dimensional shape, is an open challenge that has several applications in mesh animation, compression, and interpolation. We present a novel approach that uses the visual perception of the shape and its motion to distinguish the rigid from the deformable parts of the object. Using two-dimensional projections of the different shape poses with respect to a number of different view points, we derive a set of one-dimensional curves, which form a superset of the mesh silhouettes. Analysing these augmented silhouettes, we identify the vertices of the mesh that correspond to the deformable parts, and a subsequent clustering approach, which is based on the diffusion distance, yields a motion-based segmentation of the shape.