Shape Modeling and Applications, International Conference on (2005)
June 13, 2005 to June 17, 2005
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SMI.2005.21
Hitoshi Yamauchi , MPI Informatik
Seungyong Lee , Pohang University of Science & Technology
Yunjin Lee , Pohang University of Science & Technology
Yutaka Ohtake , Volume-CAD Development Team
Alexander Belyaev , MPI Informatik
Hans-Peter Seidel , MPI Informatik
Feature sensitive mesh segmentation is important for many computer graphics and geometric modeling applications. In this paper, we develop a mesh segmentation method which is capable of producing high-quality shape partitioning. It respects fine shape features and works well on various types of shapes, including natural shapes and mechanical parts. The method combines a procedure for clustering mesh normals with a modification of the mesh chartification technique in . For clustering of mesh normals, we adopt Mean Shift, a powerful general purpose technique for clustering scattered data. We demonstrate advantages of our method by comparing it with two state-of-the-art mesh segmentation techniques.
S. Lee, A. Belyaev, Y. Lee, Y. Ohtake, H. Yamauchi and H. Seidel, "Feature Sensitive Mesh Segmentation with Mean Shift," Proceedings. International Conference on Shape Modeling and Applications(SMI), Cambridge, MA, 2005, pp. 238--245.