Mesh Segmentation by Local Depth

In this paper, we propose a novel segmentation algorithm based on the local depth, a new measure for capturing the geometrical feature of 3D boundary points. Compared to the curvature feature, the local depth has two advantages: 1) The local depth is in itself defined on a discrete space, while the curvature is defined on a smooth space. Thus, the local depth is more suitable for capturing the geometrical feature of partial boundary on unsmooth 3D surface. 2) The local depth considers a wider range of geometry information than the curvature does, hence it avoids discovering some false boundary, and is able to find more boundaries that the curvature. Based on the local depth, we then introduce the Fast Marching Watersheds algorithm [13] to segment a mesh into representative regions.

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

[2]  Karsten P. Ulland,et al.  Vii. References , 2022 .

[3]  I. Biederman Recognition-by-components: a theory of human image understanding. , 1987, Psychological review.

[4]  Martin D. Levine,et al.  3D part segmentation using simulated electrical charge distributions , 1996, Proceedings of 13th International Conference on Pattern Recognition.

[5]  Dinesh Manocha,et al.  Interactive surface decomposition for polyhedral morphing , 1999, The Visual Computer.

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

[7]  Hans-Christian Hege,et al.  Fast and intuitive generation of geometric shape transitions , 2000, The Visual Computer.

[8]  Craig Gotsman,et al.  Spectral compression of mesh geometry , 2000, EuroCG.

[9]  Michael Garland,et al.  Hierarchical face clustering on polygonal surfaces , 2001, I3D '01.

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

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

[12]  Bruno Lévy,et al.  Least squares conformal maps for automatic texture atlas generation , 2002, ACM Trans. Graph..

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

[14]  TalAyellet,et al.  Hierarchical mesh decomposition using fuzzy clustering and cuts , 2003 .

[15]  Mongi A. Abidi,et al.  Perception-based 3D triangle mesh segmentation using fast marching watersheds , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

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

[17]  Pedro V. Sander,et al.  Multi-Chart Geometry Images , 2003, Symposium on Geometry Processing.

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

[19]  Alla Sheffer,et al.  D‐Charts: Quasi‐Developable Mesh Segmentation , 2005, Comput. Graph. Forum.

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

[21]  Y. Zhang,et al.  Content-Based 3-D Model Retrieval: A Survey , 2007, IEEE Trans. Syst. Man Cybern. Part C.

[22]  Zhang Yao,et al.  Content-Based 3-D Model Retrieval: A Survey , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[23]  Pierre Machart Morphological Segmentation , 2009 .