This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
A Flexible Similarity Measure for 3D Shapes Recognition
November 2004 (vol. 26 no. 11)
pp. 1507-1520
This paper is devoted to presenting a new strategy for 3D objects recognition using a flexible similarity measure based on the recent Modeling Wave (MW) topology in spherical models. MW topology allows us to establish an n-connectivity relationship in 3D objects modeling meshes. Using the complete object model, a study on considering different partial information of the model has been carried out to recognize an object. For this, we have introduced a new feature called Cone-Curvature (CC), which originates from the MW concept. CC gives an extended geometrical surroundings knowledge for every node of the mesh model and allows us to define a robust and adaptable similarity measure between objects for a specific model database. The defined similarity metric has been successfully tested in our lab using range data of a wide variety of 3D shapes. Finally, we show the applicability of our method presenting experimentation for recognition on noise and occlusion conditions in complex scenes.

[1] S. Santini and R. Jain, “Similarity Measures,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, no. 9, pp. 871-883, Sept. 1999.
[2] S. Antani, R. Kasturi, and R. Jain, A Survey on the Use of Pattern Recognition Methods for Abstraction, Indexing and Retrieval of Images and Video Pattern Recognition, vol. 35, pp. 945-965, 2002.
[3] R. Jain, R. Kasturi, and B.G. Schinck, Machine Vision. McGraw-Hill, 1995.
[4] R.J. Campbell and P.J. Flynn, A Survey of Free-Form Object Representation and Recognition Techniques Computer Vision and Image Understanding, vol. 81, pp. 166-210, 2001.
[5] H.-Y. Shum, M. Hebert, and K. Ikeuchi, On 3D Shape Similarity Proc. IEEE Conf. Compter Vision and Pattern Recognition, pp. 526-531, June 1966.
[6] C. Dorai and A.K. Jain, “Cosmos—A Representation Scheme for 3D Free-Form Objects,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, pp. 1115–1130, Oct. 1997.
[7] A.E. Johnson and M. Hebert, “Recognizing Objects by Matching Oriented Points,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 684-689, 1997.
[8] S.M. Yamany and A.A. Farag, “Free-Form Surface Registration Using Surface Signatures,” Proc. IEEE Int'l Conf. Computer Vision, vol. 2, pp. 1098–1104, Sept. 1999.
[9] S.M. Yamany and A.A. Farag, Surfacing Signatures: An Orientation Independent Free-Form Surface Representation Scheme for the Purpose of Objects Registration and Matching IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 8, pp. 1105-1120, Aug. 2002.
[10] C.S. Chua and R. Jarvis, Point Signatures: A New Representation for 3D Object Recognition Int'l J. Computer Vision, vol. 25, no. 1, pp. 63-85, 1997.
[11] R. Osada, T. Funkhouser, B. Chazelle, and D. Dobkin, Matching 3D Models with Shape Distributions Shape Modeling Int'l, May 2001.
[12] J.-P. Vandeborre, V. Couillet, and M. Daoudi, A Practical Approach for 3D Model Indexing by Combining Local and Global Invariants Proc. First Int'l Symp. 3D Data Processing Visualization and Transmission, pp. 644-647, 2002.
[13] A. Adán, C. Cerrada, V. Feliu, Global Shape Invariants: A Solution For 3D Object Discrimination/Identification Problem Pattern Recognition, vol. 34, pp. 1331-1348, 2001.
[14] R.C. Veltkamp, Shape Matching: Similarity Measures and Algorithms Technical Report UU-CS-2001-03, Utrecht Univ., Jan. 2001.
[15] F. Serratosa, R. Alquézar, and A. Sanfeliu, Function-Described for Modeling Objects Represented by Attributed Graphs Pattern Recognition, vol. 36, pp. 781-798, 2003.
[16] A. Sehgal and U.B. Desai, 3D Object Recognition Using Bayesian Geometric Hashing and Pose Clustering Pattern Recognition, vol. 36, pp. 765-780, 2003.
[17] B.J. Super and H. Lu, Evaluation of a Hipothesizer for Silhouette-Based 3D Object Recognition Pattern Recognition, vol. 36, pp. 69-78, 2003.
[18] C.M. Cyr and B.B. Kimia, 3D Object Recognition Using Shape Similarity-Based Aspect Graph Proc. Int'l Conf. Computer Vision, pp. 254-261, 2001.
[19] X. Liu, R. Sun, S.B. Kang, and H.Y. Shum, Directional Histogram Model for Three-Dimensional Shape Similarity Proc. Conf. Vision and Pattern Recognition, vol. 1, pp. 813-820, 2003.
[20] H. Delinguette, Simplex Meshes: A General Representation for 3D Shape Reconstruction Technical Report 2214, INRIA, France, 1994.
[21] J.J. Koenderink and A.J. Van Doorn, Surface Shape and Curvature Scales Image and Vision Computing, vol. 10, no. 8, pp. 557-556, 1992.
[22] N. Dyn, K. Hormann, S.J. Kim, and D. Levin, Optimizing 3D Triangulations Using Discrete Curvature Analysis Math. Methods for Curves and Surfaces, pp. 135-146, 2000.
[23] L. Alboul and R. VanDamme, Polyhedral Metrics in Surface Reconstruction The Mathematics of Surfaces VI, G. Mullineux, ed., pp. 171-200, 1996.
[24] A. Adán, C. Cerrada, and V. Feliú, Modeling Wave Set: Definition and Application of a new Topological Organization for 3D Object Modeling Computer Vision and Image Understanding, vol. 79, pp. 281-307, 2000.
[25] A. Adán, C. Cerrada, and V. Feliú, A Fast Mesh Deformation Method to Build Spherical Representation Model of 3D Objects Lecture Notes in Computer Science, vol. 1351, pp. 482-489, 1998.
[26] M. Hebert, K. Ikeuchi, and H. Delingette, “A Spherical Representation for Recognition of Free-Form Surfaces,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 7, p. 681, July 1995.
[27] K.M. Miettinen, Nonlinear Multiobjective Optimization. Kluwer Academic, 1999.
[28] M. Zeleny, Compromise Programming. Multiple Criteria decision Making, J.L. Cochrane and M. Zeleny, eds. Univ. of South Carolina Press, Columbia, pp. 262-301, 1973.
[29] P.L. Yu, A Class of Solutions for Group Decision Problems Management Science, vol. 19, no. 8, pp. 936-946, 1973.
[30] L. Zadeh, Optimality and Non-Scalar-Valued Performance Criteria IEEE Trans. Automatic Control, vol. 8, pp. 59-60, 1963.
[31] J.C. Bezdek and J.D. Harris, Fuzzy Partitions and Relations: an Axiomatic Basis for Clustering Fuzzy Sets and Systems, vol. 1, pp. 111-127, 1978.
[32] A. Adán, S. Salamanca, and C. Cerrada, Reconstruction of Spherical Models From Multiple Partial Models Proc. First Int'l Symp. 3D Data Processing Visualization and Transmission, pp. 532-536, 2002.
[33] P. Merchán, A. Adán, S. Salamanca, and C. Cerrada, 3D Complex Scenes Segmentation From a Single Range Image Using Virtual Exploration Lecture Notes in Artificial Intelligence, vol. 2527, pp. 923-932, 2002.

Index Terms:
Computer vision, feature measurement, object recognition, similarity measures, pattern recognition.
Citation:
Antonio Ad?, Miguel Ad?, "A Flexible Similarity Measure for 3D Shapes Recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 11, pp. 1507-1520, Nov. 2004, doi:10.1109/TPAMI.2004.94
Usage of this product signifies your acceptance of the Terms of Use.