Fast mesh segmentation using random walks

3D mesh models are now widely available for use in various applications. The demand for automatic model analysis and understanding is ever increasing. Mesh segmentation is an important step towards model understanding, and acts as a useful tool for different mesh processing applications, e.g. reverse engineering and modeling by example. We extend a random walk method used previously for image segmentation to give algorithms for both interactive and automatic mesh segmentation. This method is extremely efficient, and scales almost linearly with increasing number of faces. For models of moderate size, interactive performance is achieved with commodity PCs. It is easy-to-implement, robust to noise in the mesh, and yields results suitable for downstream applications for both graphical and engineering models.

[1]  Donald D. Hoffman,et al.  Salience of visual parts , 1997, Cognition.

[2]  Tamás Várady,et al.  Direct segmentation of smooth, multiple point regions , 2002, Geometric Modeling and Processing. Theory and Applications. GMP 2002. Proceedings.

[3]  Paul J. Besl,et al.  Direct construction of polynomial surfaces from dense range images through region growing , 1995, TOGS.

[4]  Shi-Min Hu,et al.  Robust principal curvatures on multiple scales , 2006, SGP '06.

[5]  Herbert Edelsbrunner,et al.  Hierarchical Morse—Smale Complexes for Piecewise Linear 2-Manifolds , 2003, Discret. Comput. Geom..

[6]  Leo Grady,et al.  Random Walks for Image Segmentation , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Daniel Cohen-Or,et al.  Intelligent mesh scissoring using 3D snakes , 2004, 12th Pacific Conference on Computer Graphics and Applications, 2004. PG 2004. Proceedings..

[8]  Marco Attene,et al.  Hierarchical mesh segmentation based on fitting primitives , 2006, The Visual Computer.

[9]  Ralph R. Martin,et al.  Random walks for mesh denoising , 2007, Symposium on Solid and Physical Modeling.

[10]  Hao Zhang,et al.  Segmentation of 3D meshes through spectral clustering , 2004, 12th Pacific Conference on Computer Graphics and Applications, 2004. PG 2004. Proceedings..

[11]  Tamás Várady,et al.  Automatic Extraction of Surface Structures in Digital Shape Reconstruction , 2006, GMP.

[12]  Ayellet Tal,et al.  Polyhedral surface decomposition with applications , 2002, Comput. Graph..

[13]  Tiow Seng Tan,et al.  Decomposing polygon meshes for interactive applications , 2001, I3D '01.

[14]  Steven J. Gortler,et al.  Fast exact and approximate geodesics on meshes , 2005, ACM Trans. Graph..

[15]  Szymon Rusinkiewicz,et al.  Modeling by example , 2004, SIGGRAPH 2004.

[16]  Ayellet Tal,et al.  Hierarchical mesh decomposition using fuzzy clustering and cuts , 2003, ACM Trans. Graph..

[17]  Hans-Peter Seidel,et al.  Mesh scissoring with minima rule and part salience , 2005, Comput. Aided Geom. Des..

[18]  Alexandru Telea,et al.  Skeleton-based Hierarchical Shape Segmentation , 2007, IEEE International Conference on Shape Modeling and Applications 2007 (SMI '07).

[19]  Daniel Cohen-Or,et al.  SnapPaste: an interactive technique for easy mesh composition , 2006, The Visual Computer.

[20]  Ayellet Tal,et al.  Metamorphosis of Polyhedral Surfaces using Decomposition , 2002, Comput. Graph. Forum.

[21]  Ralph R. Martin,et al.  Reverse engineering of geometric models - an introduction , 1997, Comput. Aided Des..

[22]  Hans-Peter Seidel,et al.  Feature sensitive mesh segmentation with mean shift , 2005, International Conference on Shape Modeling and Applications 2005 (SMI' 05).

[23]  Ross T. Whitaker,et al.  Partitioning 3D Surface Meshes Using Watershed Segmentation , 1999, IEEE Trans. Vis. Comput. Graph..

[24]  Sunil Arya,et al.  ANN: library for approximate nearest neighbor searching , 1998 .

[25]  Ariel Shamir.  Geodesic Mean Shift , 2004 .

[26]  Leonidas J. Guibas,et al.  Shape segmentation using local slippage analysis , 2004, SGP '04.

[27]  Paul S. Heckbert,et al.  Using particles to sample and control implicit surfaces , 1994, SIGGRAPH Courses.

[28]  Donald D. Hoffman,et al.  Parts of recognition , 1984, Cognition.

[29]  Marco Attene,et al.  Mesh Segmentation - A Comparative Study , 2006, IEEE International Conference on Shape Modeling and Applications 2006 (SMI'06).

[30]  J. Mitani,et al.  Making papercraft toys from meshes using strip-based approximate unfolding , 2004, SIGGRAPH 2004.

[31]  Paul S. Heckbert,et al.  Using particles to sample and control implicit surfaces , 1994, SIGGRAPH.

[32]  Hao Zhang,et al.  Sub-sampling for Efficient Spectral Mesh Processing , 2006, Computer Graphics International.

[33]  Shi-Min Hu,et al.  Robust Feature Classification and Editing , 2007, IEEE Transactions on Visualization and Computer Graphics.

[34]  W. D. Cairns.  THE MATHEMATICAL ASSOCIATION OF AMERICA. , 1917, Science.

[35]  Ayellet Tal,et al.  Mesh segmentation using feature point and core extraction , 2005, The Visual Computer.