Hierarchical Mesh Segmentation Based on Global Sharp Vertices
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초록
In this paper, we propose a hierarchical method for segmenting a given 3D mesh, which hierarchically clusters sharp vertices of the mesh using the metric of geodesic distance among them. Sharp vertices are extracted from the mesh by analyzing convexity that reflects global geometry. As well as speeding up the computing time, the sharp vertices of this kind avoid the problem of local optima that may occur when feature points are extracted by analyzing the convexity that reflects local geometry. For obtaining more effective results, the sharp vertices are categorized according to the priority from the viewpoint of cognitive science, and the reasonable number of clusters is automatically determined by analyzing the geometric features of the mesh.
Abstract
In this paper, we propose a hierarchical method for segmenting a given 3D mesh, which hierarchically clusters sharp vertices of the mesh using the metric of geodesic distance among them. Sharp vertices are extracted from the mesh by analyzing convexity that reflects global geometry. As well as speeding up the computing time, the sharp vertices of this kind avoid the problem of local optima that may occur when feature points are extracted by analyzing the convexity that reflects local geometry. For obtaining more effective results, the sharp vertices are categorized according to the priority from the viewpoint of cognitive science, and the reasonable number of clusters is automatically determined by analyzing the geometric features of the mesh.
참고문헌 (27)
- B. Chazelle, "Strategies for polyhedral surface decomposition: an experimental study", Computational Geometry: Theory and Applications, 7, pp.327~342 (1997)
- M. Attene, "Mesh segmentation - a comparative study", IEEE Int. Conf. on Shape Modeling and Applications, pp.14~25 (2006)
- D. L. Page, "Perception based 3D triangle mesh segmentation using fast matching watersheds", Conference on Computer Vision and Pattern Recognition, pp.27~32 (2003)
- T. Srinak, "A novel method for 3D surface mesh segmentation", Proc. of the 6th IASTED International Conference on Computers, pp.212~217 (2003)
- M. Garland, "Hierarchical face clustering on polygonal surfaces", Proc. of the 2001 Symposium on Interactive 3D Graphics, pp.49~58 (2001)
- S. Katz, "Hierarchical mesh decomposition using fuzzy clustering and cuts", ACM Transactions on Graphics (TOG), 22(3), pp.954~961 (2003)
- T. Kanungo, "An efficient -means clustering algorithm: analysis and implementation", IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(7), pp.881~892 (2002)
- A. P. Mangan, "Partitioning 3D surface meshes using watershed segmentation", IEEE Transactions on Visualization and Computer Graphics, 5(4), pp.308~321 (1999)
- T. K. Dey, "Shape segmentation and matching with flow discretization", Proc. of the Workshop on Algorithms and Data Structures (WADS), pp.25~36 (2003)
- K. Wu, "3D part segmentation using simulated electrical charge distributions", Proc. of the 1996 IEEE International Conference on Pattern Recognition (ICPR), pp.14~18 (1996)
- D. Cohen-Steiner, "Variational shape approximation", Proc. of the 31st Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH), pp.27~34 (2004)
- Y. Zhou, "Decomposing polygon meshes by means of critical points", Proc. of MMM'04, pp.187~195 (2004)
- M. Mortara, "Blowing bubbles for the multi-scale analysis and decomposition of triangle meshes", Algorithmica, Special Issues on Shape Algorithms, 38(2), pp.227~224 (2004)
- S. Katz, "Mesh segmentation using feature points and core extraction", Visual Computer, 21, pp.649~658 (2005)
- Approximate convex decomposition of polyhedra, "J. M. Lien", Texas A&M University, ~, pp.Technical Report TR06-002 (2006)
- D. D. Hoffman, "Parts of recognition", Cognition, 18 (1984)
- D. D. Hoffman, "Salience of visual parts", Cognition, 63 (1997)
- F. Yamaguchi, "Curves and surfaces in Computer Aided Geometric Design" (1988), Springer-Berlag
- G. Taubin, "Estimating the tensor of curvatures of a surface from a polyhedral approximation", Proc. of International Conf. on Computer Vision (1995)
- A. Rosenfeld, "Angle detection in digital curves", IEEE Transactions on Computers, 22, pp.875~878 (1973)
- A.D.C. Smith, "The Folding of the Human Brain: from Shape to Function", 박사, pp.1999
- S. C. Johnson, "Hierarchical Clustering Schemes", Psychometrika, 2, pp.241~254 (1967)
- E. W. Dijkstra, "A note on two problems in connection with graphs", Numerische Mathematik, 1, pp.269~271 (1959)
- D. Cohen-Steiner, "Restricted Delaunay triangulations and normal cycle", Proc. of 19th Annual ACM Sym. on Computational Geometry, pp.237~246 (2003)
- "Computational geometry algorithm library"[URL]
- P. Shilane, "The Princeton shape benchmark", Proc. of Shape Modeling International (2004)
- Y. J. Park, "Mesh segmentation with the geodesic means of clustering of sharp vertices,” IASTED08", ~ (2008)