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Identifying flat and tubular regions of a shape by unstable manifolds
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Source ACM Symposium on Solid and Physical Modeling archive
Proceedings of the 2006 ACM symposium on Solid and physical modeling table of contents
Cardiff, Wales, United Kingdom
SESSION: Shape segmentation table of contents
Pages: 27 - 37  
Year of Publication: 2006
ISBN:1-59593-358-1
Authors
Samrat Goswami  U. Texas at Austin, Austin, TX
Tamal K. Dey  Ohio State U., Columbus, OH
Chandrajit L. Bajaj  U. Texas at Austin, Austin, TX
Sponsor
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
Publisher
ACM  New York, NY, USA
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ABSTRACT

We present an algorithm to identify the flat and tubular regions of a three dimensional shape from its point sample. We consider the distance function to the input point cloud and the Morse structure induced by it on R3. Specifically we focus on the index 1 and index 2 saddle points and their unstable manifolds. The unstable manifolds of index 2 saddles are one dimensional whereas those of index 1 saddles are two dimensional. Mapping these unstable manifolds back onto the surface, we get the tubular and flat regions. The computations are carried out on the Voronoi diagram of the input points by approximating the unstable manifolds with Voronoi faces. We demonstrate the performance of our algorithm on several point sampled objects.


REFERENCES

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1
 
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Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T., Weissig, H., Shindyalov, I., and Bourne, P. 2000. The protein data bank. Nucleic Acids Research, 235--242.
 
3
Bernardini, F., Bajaj, C., Chen, J., and Schikore, D. 1999. Automatic reconstruction of 3d cad models from digital scans. Int. J. on Comp. Geom. and Appl. 9, 4--5, 327--369.
 
4
CGAL CONSORTIUM. CGAL: Computational Geometry Algorithms Library. http://www.cgal.org.
 
5
 
6
Chazal, F., and Lieutier, A. 2004. Stability and homotopy of a subset of the medial axis. In Proc. 9th ACM Sympos. Solid Modeling and Applications, 243--248.
 
7
COCONE. Tight Cocone Software for surface reconstruction and medial axis approximation. http://www.cse.ohio-state.edu/~tamaldey/cocone.html.
8
 
9
Dey, T. K., and Goswami, S. 2004. Provable surface reconstruction from noisy samples. In Proc. 20th ACM-SIAM Sympos. Comput. Geom., 330--339.
 
10
 
11
Dey, T. K., Giesen, J., and Goswami, S. 2003. Shape segmentation and matching with flow discretization. In Proc. Workshop Algorithms Data Strucutres (WADS 03), F. Dehne, J.-R. Sack, and M. Smid, Eds., LNCS 2748, 25--36.
 
12
Dey, T. K., Giesen, J., Ramos, E., and Sadri, B. 2005. Critical points of the distance to an epsilon-sampling of a surface and flow-complex-based surface reconstruction. In Proc. 21st ACM-SIAM Sympos. Comput. Geom., 218--227.
 
13
Edelsbrunner, H. 2002. Surface reconstruction by wrapping finite point sets in space. In Ricky Pollack and Eli Goodman Festschrift, B. Aronov, S. Basu, J. Pach, and M. Sharir, Eds. Springer-Verlag, 379--404.
 
14
15
 
16
 
17
Mortara, M., Patanè, G., Spagnuolo, M., Falcidieno, B., and Rossignac, J. 2004. Plumber: a multi-scale decomposition of 3d shapes into tubular primitives and bodies. In Proc. 9th ACM Sympos. Solid Modeling and Applications, 139--158.
 
18
Pottmann, H., Hofer, M., Odehnal, B., and Wallner, J. 2004. Line geometry for 3d shape understanding and reconstruction. Computer Vision - ECCV 3021, 1, 297--309.
 
19
Shinagawa, Y., Kunni, T., Belayev, A., and Tsukioka, T. 1996. Shape modeling and shape analysis based on singularities. Internat. J. Shape Modeling 2, 85--102.
 
20
 
21
Várady, T., Martin, R., and Cox, J. 1997. Reverse engineering of geometric models - an introduction. Computer Aided Design 29, 255--268.
 
22
Verroust, A., and Lazarus, F. 2000. Extracting skeletal curves from 3d scattered data. The Visual Computer 16, 15--25.
 
23
Wu, J., and Kobbelt, L. 2005. Structure recovery via hybrid variational surface approximation. Computer Graphics Forum 24, 3, 277--284.


Collaborative Colleagues:
Samrat Goswami: colleagues
Tamal K. Dey: colleagues
Chandrajit L. Bajaj: colleagues