This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
3-D object recognition with symmetric models: symmetry extraction and encoding
August 1994 (vol. 16 no. 8)
pp. 814,815,816,817,818
Object recognition systems which employ solid models and range data have been a topic of interest for several years. Model databases have the potential to become large in some environments. This paper proposes a pair of techniques for incorporating knowledge of the symmetries of object models into the recognition process. The effects of symmetric models on the speed of an object recognition system is examined in the context of an implemented system employing invariant feature indexing as a correspondence-building mechanism. Groups of model surfaces are enumerated and examined to yield a list of segment label permutations which summarize the model's symmetry. This symmetry extraction process is followed by a symmetry encoding procedure which replaces groups of features which are indistinguishable because of symmetry with a single prototype feature group. Experiments with a large model database demonstrate the utility of these symmetry extraction and encoding techniques.<>

[1] H. Alt, K. Melhorn, H. Wagner, and E. Welzl, "Congruence, similarity, and symmetries of geometric objects,"Discrete and Computational Geometry, vol. 3, pp. 237-256, 1988.
[2] F. Arman and J. Aggarwal, "Automatic generation of recognition strategies using CAD models," inProc. IEEE Workshop on Directions in Automat. CAD-Based Vision, Maui, HI, 1991, pp. 124-133.
[3] M. J. Atallah, "On symmetry detection,"IEEE Trans. Comput., vol. C-34, no. 7, pp. 663-666, July 1985.
[4] A. Boardman, D. O'Connor, and P. Young,Symmetry and its Applications in Science. New York: Wiley, 1973.
[5] J. B. Burns and L. J. Kitchen, "Rapid object recognition from a large model base using prediction hierarchies," inProc. 1988 DARPA Image Understanding Workshop, 1988 pp. 711-719.
[6] C. H. Chen and A. C. Kak, "A robot vision system for recognizing 3-D objects in low-order polynomial time,"IEEE Trans. Syst., Man Cybern., vol. 19, no. 6, pp. 1535-1563, Nov./Dec. 1989.
[7] S. J. Dickinson, A. P. Pentland, and A. Rosenfeld, "From volumes to views: An approach to 3-D object recognition," inProc. IEEE Workshop CAD-Based Vision(Maui, HI), June 1991.
[8] P. J. Flynn, "Saliencies and symmetries: toward 3D object recognition from large model databases," inProc. IEEE Comput. Soc. Conf. Comput. Vision and Pattern Recognit., Champaign, IL, June 1992, pp. 322-327.
[9] P. J. Flynn and A. K. Jain, "BONSAI: 3D Object Recognition Using Constrained Search,"IEEE Trans. Pattern Anal. Machine Intell., vol. 13, no. 10, pp. 1066-1075, Oct. 1991.
[10] P. J. Flynn and A. K. Jain, "CAD-based computer vision: from CAD models to relational graphs,"IEEE Trans. Pattern Anal. Machine Intell., vol. 13, no. 2, pp. 114-132, Feb. 1991.
[11] P. J. Flynn and A. K. Jain, "3D object recognition using invariant feature indexing of interpretation tables,"Comput. Vision, Graphics, and Image Processing: Image Understanding, vol. 55, no. 2, pp. 119-129, Mar. 1992.
[12] W.E.L. Grimson,Object Recognition by Computer: The Role of Geometric Constraints, MIT Press, Cambridge, Mass., 1990.
[13] W. E. L. Grimson and T. Lozano-Pérez, "Model-based recognition and localization from sparse range or tactile data,"Int. J. Robotics Res., vol. 3, no. 3, pp. 3-35, Fall 1984.
[14] C. Hansen and T. Henderson, "CAGD-based computer vision,"IEEE Trans. Pattern Anal. Machine Intell., vol. 11, no. 11, pp. 1181-1193, Nov. 1989.
[15] K. Ikeuchi and T. Kanade, "Automatic generation of object recognition programs,"Proc. IEEE, vol. 76, no. 8, pp. 1016-1035, Aug. 1988.
[16] A. K. Jain and R. L. Hoffman, "Evidence-based recognition of 3-D objects,"IEEE Trans. Pattern Anal. Machine Intell., vol. 10, no. 6, pp. 783-802, Nov. 1988.
[17] X. Jiang and H. Bunke, "A simple and efficient algorithm for determining the symmetries of polyhedra,"Comput. Vision, Graphics, and Image Processing: Graphical Models and Image Processing, vol. 54, no. 1, pp. 91-95, Jan. 1992.
[18] W.-Y. Kim and A. C. Kak, "3-D object recognition using bipartite matching embedded in discrete relaxation",IEEE Trans. Pattern Anal. Machine Intell., vol. 13, no. 3, pp. 224-251, 1991.
[19] L. Stark and K. Bowyer, "Genetic recognition through qualitative reasoning about 3-d shape and object function," inProc. IEEE Comput. Soc. Conf. Comput. Vision and Pattern Recognit., 1991, pp. 251-256.
[20] M. Swain, "Object recognition from a large database using a decision tree," inProc. DARPA Image Understanding Workshop, 1988, pp. 690-696.
[21] A. Vayda and A. Kak, "A robot vision systems for recognition of generic shaped objects,"Comput. Vision, Graphics, and Image Processing: Image Understanding, vol. 54, no. 1, pp. 1-46, July 1991.
[22] S. Warshal, "A theorem on Boolean matrices,"J. ACM, vol. 9, 1962.

Index Terms:
Object recognition,Encoding,Indexing,Spatial databases,Solid modeling,Image recognition,Data mining,Computer vision,Machine intelligence,Context modeling
Citation:
"3-D object recognition with symmetric models: symmetry extraction and encoding," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, no. 8, pp. 814,815,816,817,818, Aug. 1994, doi:10.1109/34.308477
Usage of this product signifies your acceptance of the Terms of Use.