Modelbase Partitioning Using Property Matrix Spectra

Computer Vision and Image Understanding

Volumn 70, Issue 2, 1998, Pages 177-196

  Sengupta, Kuntal ^a   Boyer, Kim L ^a  

^a Ohio State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER AIDED DESIGN; EIGENVALUES AND EIGENFUNCTIONS; GRAPH THEORY; IMAGE QUALITY; IMAGE SEGMENTATION; MATHEMATICAL MODELS; PERTURBATION TECHNIQUES;

PROPERTY MATRIX SPECTRA; SPECTRAL BASED REPRESENTATION;

OBJECT RECOGNITION;

EID: 0032070761     PISSN: 10773142     EISSN: None     Source Type: Journal    
DOI: 10.1006/cviu.1997.0631     Document Type: Article

References (32)

1. K. Sengupta and K. L. Boyer, Organizing large structural modelbases, IEEE Trans. Pattern Anal. Machine Intell. 17, 1995, 321-332.
2. J. Ponce et al., Object representation for object recognition, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1994, pp. 147-152.
3. Y. Lamdan, J. T. Schwartz, and H. J. Wolfson, Affine invariant model based object recognition, IEEE Trans. Robotics Automation 6(5), 1990, 578-589.
4. D. T. Clemens and D. W. Jacobs, Space and time bounds on indexing 3-D models from 2-D images, IEEE Trans. Pattern Anal. Machine Intell. 13, 1991, 1007-1017.
5. W. E. L. Grimson, D. P. Huttenlocher, and D. W. Jacobs, Affine Matching with Bounded Sensor Error: A Study of Geometric Hashing and Alignment, Tech. Rep. A.I. Memo 1250, MIT Artificial Intelligence Laboratory, Aug. 1991.
6. J. Mao, P. J. Flynn, and A. K. Jain, Integration of multiple feature groups and multiple views into 2D object recognition system, Comput. Vision Image Understanding 62, 1995, 309-325.
7. L. Grewe and A. Kak, Interactive learning of a multiple-attribute hash table classifier for fast object recognition, Comput. Vision Image Understanding 61, 1995, 387-416.
8. K. Sengupta and K. L. Boyer, Using geometric hashing with information theoretic clustering for fast recognition from a large CAD modelbase, in Proceedings of the IEEE International Symposium on Computer Vision, 1995, pp. 151-156.
9. M. Costa and L. G. Shapiro, Scene analysis using appearance-based models and relational indexing, in Proceedings of the IEEE International Symposium on Computer Vision, 1995, pp. 103-108.
10. K. L. Boyer and A. C. Kak, Structural stereo for 3-D vision, IEEE Trans. Pattern Anal. Machine Intell. 10, 1988, 144-166.
11. A. Wong and M. You, Entropy and distance of random graphs with application to structural pattern recognition, IEEE Trans. Pattern Anal. Machine Intell. 7, 1985, 599-609.
12. R. Nevatia and T. Binford, Description and recognition of curved objects, Artificial Intell. 8, 1977, 77-98.
13. C. Dorai and A. K. Jain, Cosmos - A representation scheme for free form objects, in International Conference on Computer Vision, 1995, pp. 1024-1029.
14. H. Sossa and R. Horaud, Model indexing: The graph-hashing approach, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1992, pp. 811-815.
15. R. Merris, The second immanantal polynomial and the centroid of a graph, SIAM J. Algebraic Discrete Methods 7, 1986, 484-503.
16. S. Sarkar and K. L. Boyer, Perceptual organization using Bayesian networks, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 1992, pp. 251-256.
17. S. Sarkar and K. L. Boyer, Quantitative measure of change based on feature organization: Eigenvalues and eigenvectors, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1996, pp. 478-483.
18. M. A. Turk and A. P. Pentland, Face recognition using eigenfaces, in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1991, pp. 586-591.
19. B. S. Manjunath, S. Chandrasekaran, and Y. F. Wang, An eigenspace update algorithm for image analysis, in Proceedings of the IEEE International Symposium on Computer Vision, 1995, pp. 551-556.
20. A. H. Tewfik and M. Deriche, An eigenstructure approach to edge detection, IEEE Trans. Image Process. 2, 1993, pp. 353-368.
21. D. B. Goldgof, H. Lee, and T. S. Huang, Matching and motion estimation of three dimensional point and line sets using eigenstructures without correspondence, Pattern Recognit. 25, 1992, pp. 271-286.
22. D. M. Cvetkovic, M. Doob, and H. Sachs, Spectra of Graphs, Academic Press, New York, 1979.
23. R. A. Horn and C. R. Johnson, Matrix Analysis, Cambridge Univ. Press, Cambridge, MA, 1985.
24. M. L. Mehta, Random Matrices, Academic Press, San Diego, 1991.
25. J. vom Scheidt and W. Purkert, Random Eigenvalues Problems, North Holland, New York, 1993.
26. S. Sarkar and K. L. Boyer, Integration, inference, and management of spatial information using Bayesian networks: Perceptual organization, IEEE Trans. Pattern Anal. Machine Intell. 15, 1993, 256-274. [Special Issue on Probabilistic Reasoning]
27. A. K. Jain and R. Dubes, Algorithms for Clustering Data, Information and System Sciences Series, Prentice Hall Advanced Reference Series, Prentice Hall, Englewood Cliffs, NJ, 1988.
28. K. Sengupta, Organizing Large Structural Modelbases, Master's thesis, The Ohio State University, 1992.
29. P. J. Flynn and A. K. Jain, BONSAI: 3D object recognition using constrained search, in International Conference on Computer Vision, 1990, pp. 263-267.
30. R. B. Fisher, From Surfaces to Objects: Computer Vision and Three-Dimensional Scene Analysis, Wiley, New York, 1989.
31. G. H. Golub and C. F. V. Loan, Matrix Computations, pp. 414-415. The Johns Hopkins Univ. Press, Baltimore, 1989.
32. K. Sengupta, Object Recognition Using Large Modelbases, Ph.D dissertation, The Ohio State University, 1996.