Fast mesh segmentation using random walks
Proceedings of the 2008 ACM symposium on Solid and physical modeling
2D Shape Decomposition Based on Combined Skeleton-Boundary Features
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
Harmonic 1-form based skeleton extraction from examples
Graphical Models
Rapid and effective segmentation of 3D models using random walks
Computer Aided Geometric Design
Automatic Segmentation of Scanned Human Body Using Curve Skeleton Analysis
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
An Automatic Correction of Ma's Thinning Algorithm Based on P-simple Points
Journal of Mathematical Imaging and Vision
Segmenting simplified surface skeletons
DGCI'08 Proceedings of the 14th IAPR international conference on Discrete geometry for computer imagery
Shape decomposition and understanding of point cloud objects based on perceptual information
Proceedings of the 9th ACM SIGGRAPH Conference on Virtual-Reality Continuum and its Applications in Industry
SMI 2011: Full Paper: An approach to automated decomposition of volumetric mesh
Computers and Graphics
Using the skeleton for 3D object decomposition
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
From the zones of influence of skeleton branch points to meaningful object parts
DGCI'13 Proceedings of the 17th IAPR international conference on Discrete Geometry for Computer Imagery
Coarse-to-fine skeleton extraction for high resolution 3D meshes
Computer Vision and Image Understanding
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We present an effective framework for segmenting 3D shapes into meaningful components using the curve skeleton. Our algorithm identifies a number of critical points on the curve skeleton, either fully automatically as the junctions of the curve skeleton, or based on user input. We use these points to construct a partitioning of the object surface using geodesics. Because it is based on the curve skeleton, our segmentation intrinsically reflects the shape symmetry and topology. By using geodesics we obtain segments that have smooth, minimally twisting borders. Finally, we present a hierarchical segmentation of shapes which reflects the hierarchical structure of the curve skeleton. We describe a voxel-based implementation of our method which is robust and noise resistant, computationally efficient, able to handle shapes of complex topology, and which delivers levelof- detail segmentations. We demonstrate the framework on various real-world 3D shapes.