Salient geometric features for partial shape matching and similarity

This article introduces a method for partial matching of surfaces represented by triangular meshes. Our method matches surface regions that are numerically and topologically dissimilar, but approximately similar regions. We introduce novel local surface descriptors which efficiently represent the geometry of local regions of the surface. The descriptors are defined independently of the underlying triangulation, and form a compatible representation that allows matching of surfaces with different triangulations. To cope with the combinatorial complexity of partial matching of large meshes, we introduce the abstraction of salient geometric features and present a method to construct them. A salient geometric feature is a compound high-level feature of nontrivial local shapes. We show that a relatively small number of such salient geometric features characterizes the surface well for various similarity applications. Matching salient geometric features is based on indexing rotation-invariant features and a voting scheme accelerated by geometric hashing. We demonstrate the effectiveness of our method with a number of applications, such as computing self-similarity, alignments, and subparts similarity.

[1]  Martial Hebert,et al.  Fully automatic registration of multiple 3D data sets , 2003, Image Vis. Comput..

[2]  D. O. Hebb,et al.  The organization of behavior , 1988 .

[3]  Pierre Alliez,et al.  Anisotropic polygonal remeshing , 2003, ACM Trans. Graph..

[4]  S. Rusinkiewicz Estimating curvatures and their derivatives on triangle meshes , 2004 .

[5]  John Hart,et al.  ACM Transactions on Graphics , 2004, SIGGRAPH 2004.

[6]  Sven J. Dickinson,et al.  Skeleton based shape matching and retrieval , 2003, 2003 Shape Modeling International..

[7]  Natraj Iyer,et al.  A RECONFIGURABLE 3D ENGINEERING SHAPE SEARCH SYSTEM PART I: SHAPE REPRESENTATION , 2003 .

[8]  Dietmar Saupe,et al.  3D Model Retrieval with Spherical Harmonics and Moments , 2001, DAGM-Symposium.

[9]  George Cybenko,et al.  Pattern Recognition of 3D CAD Objects: Towards an Electronic Yellow Pages of Mechanical Parts , 1996 .

[10]  Dietmar Saupe,et al.  Tools for 3D-object retrieval: Karhunen-Loeve transform and spherical harmonics , 2001, 2001 IEEE Fourth Workshop on Multimedia Signal Processing (Cat. No.01TH8564).

[11]  Hans-Peter Seidel,et al.  Ridge-valley lines on meshes via implicit surface fitting , 2004, ACM Trans. Graph..

[12]  Taku Komura,et al.  Topology matching for fully automatic similarity estimation of 3D shapes , 2001, SIGGRAPH.

[13]  S. Vadlamani On the Diffusion of Shape , 2007 .

[14]  D. Kendall The diffusion of shape , 1977, Advances in Applied Probability.

[15]  Sylvain Petitjean,et al.  A survey of methods for recovering quadrics in triangle meshes , 2002, CSUR.

[16]  Kin Hing Ho,et al.  3D model search engine , 2007 .

[17]  Andrew E. Johnson,et al.  Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Cohen-OrDaniel,et al.  Salient geometric features for partial shape matching and similarity , 2006 .

[19]  Michael Elad,et al.  Content Based Retrieval of VRML Objects - An Iterative and Interactive Approach , 2001, Eurographics Multimedia Workshop.

[20]  Michael Elad,et al.  Content based retrieval of VRML objects: an iterative and interactive approach , 2002 .

[21]  H. Seidel,et al.  Ridge-valley lines on meshes via implicit surface fitting , 2004, SIGGRAPH 2004.

[22]  Jitendra Malik,et al.  Recognizing Objects in Range Data Using Regional Point Descriptors , 2004, ECCV.

[23]  Szymon Rusinkiewicz,et al.  Estimating curvatures and their derivatives on triangle meshes , 2004, Proceedings. 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004..

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

[25]  Martial Hebert,et al.  Parts-based 3D object classification , 2004, CVPR 2004.

[26]  Haim J. Wolfson,et al.  Geometric hashing: an overview , 1997 .

[27]  Szymon Rusinkiewicz,et al.  Modeling by example , 2004, ACM Trans. Graph..

[28]  Yehezkel Lamdan,et al.  Geometric Hashing: A General And Efficient Model-based Recognition Scheme , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[29]  Remco C. Veltkamp,et al.  A survey of content based 3D shape retrieval methods , 2004, Proceedings Shape Modeling Applications, 2004..

[30]  H. Barlow Vision: A computational investigation into the human representation and processing of visual information: David Marr. San Francisco: W. H. Freeman, 1982. pp. xvi + 397 , 1983 .

[31]  Ming Ouhyoung,et al.  A 3D Object Retrieval System Based on Multi-Resolution Reeb Graph , 2002 .

[32]  Ryutarou Ohbuchi,et al.  Shape-similarity search of 3D models by using enhanced shape functions , 2005, Int. J. Comput. Appl. Technol..

[33]  Remco C. Veltkamp,et al.  State of the Art in Shape Matching , 2001, Principles of Visual Information Retrieval.

[34]  Szymon Rusinkiewicz,et al.  Shape matching and anisotropy , 2004, ACM Trans. Graph..

[35]  Bf Buxton,et al.  Three-Dimensional Surface Curvature Estimation using Quadric Surface Patches , 2002 .

[36]  David P. Dobkin,et al.  A search engine for 3D models , 2003, TOGS.

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

[38]  E. Capaldi,et al.  The organization of behavior. , 1992, Journal of applied behavior analysis.

[39]  Bernard Chazelle,et al.  Matching 3D models with shape distributions , 2001, Proceedings International Conference on Shape Modeling and Applications.

[40]  W TangelderJohan,et al.  A survey of content based 3D shape retrieval methods , 2008 .

[41]  Martial Hebert,et al.  On 3D shape similarity , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[42]  Szymon Rusinkiewicz,et al.  Rotation Invariant Spherical Harmonic Representation of 3D Shape Descriptors , 2003, Symposium on Geometry Processing.

[43]  Thomas A. Funkhouser,et al.  The Princeton Shape Benchmark , 2004, Proceedings Shape Modeling Applications, 2004..

[44]  K. Mardia,et al.  Statistical Shape Analysis , 1998 .