Multidimensional Indexing for Recognizing Visual Shapes

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 16, Issue 4, 1994, Pages 373-392

  Califano, Andrea ^a   Mohan, Rakesh ^a  

^a IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATION THEORY; COMPUTER VISION; DATABASE SYSTEMS; FAULT TOLERANT COMPUTER SYSTEMS; TABLE LOOKUP;

HIGH DIMENSIONAL GLOBAL INVARIANTS; MULTIDIMENSIONAL INDEXING; OBJECT RECOGNITION TIME; TWO DIMENSIONAL SHAPE ACQUISITION; VISUAL SHAPE RECOGNITION;

PATTERN RECOGNITION;

EID: 0028405552     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/34.277591     Document Type: Article

References (58)

1. H. Asada and M. Brady, “The curvature primal sketch,” IEEE Trans. Pattern Anal. Machine Intell., vol. 8, no. 1, 1986.
2. N. Ayache, O. Faugeras, and B. Faverjon, “A geometric matcher for recognizing and positioning 3D rigid objects,” Int. Conf. Intelligent Robots and Computer Vision, Proc. SPIE, Oct. 1984.
3. D. H. Ballard, “Parameter nets: A theory of low level vision,” in Proc. 7th Int. Joint Conf. Artificial Intelligence, Aug. 1981, pp. 1068–1078.
4. “Generalizing the Hough transform to detect arbitrary shapes,” Pattern Recogn., vol. 13, no. 2, 1981, pp. 111–122.
5. R. M. Bolle, A. Califano, R. Kjeldsen, and R. W. Taylor, “Computer vision research,” in Proc. DARPA Image Understanding Workshop, Palo Alto, CA, May 1989.
6. R. M. Bolle, A. Califano, R. Kjeldsen, and R. W. Taylor, “Visual recognition using concurrent and layered parameter networks,” in Proc. IEEE Conf. Computer Vision and Pattern Recognition, San Diego, June 1989.
7. B. Bhanu and O. D. Faugeras, “Shape matching of two-dimensional objects,” IEEE Trans. Pattern Anal. Machine Intell., vol. 8, no. 2, pp. 137–155, Mar. 1984.
8. P. J. Best and R. C. Jain, “Three-dimensional object recognition,” Comput. Surveys, vol. 17, no. 1, pp. 75–145, Mar. 1985.
9. A. P. Blicher, “A shape representation based on geometric topology: Bumps, Gaussian curvature, and the topological zodiac,” in Proc. 10th Int. Joint Conf. Artificial Intelligence, Aug. 1987, pp. 767–770.
10. R. C. Bolles and R. A. Cain, “Recognizing and locating partially visible objects: The local feature focus approach,” Int. J. Robotics Research, vol. 1, no. 3, pp. 57–82, Fall 1982.
11. R. C. Bolles, P. Horaud, and M. J. Hannah, “3DPO: A three-dimensional dimensional part orientation system,” in Proc. 8th Int. Joint Conf on Artificial Intelligence, Aug. 1983, pp. 1116–1120.
12. R. A. Brooks, “Model-based three-dimensional interpretations of two-dimensional dimensional images,” IEEE Trans. Pattern Anal. Machine Intell., vol. 5, no. 2, pp. 140–150, Mar. 1983.
13. P. J. Burt, “Smart sensing within a pyramid vision machine,” Proc. IEEE, vol. 76, no. 8, pp. 1006–1015, Aug. 1988.
14. J. F. Canny, “A computational approach to edge detection,” IEEE Trans. Pattern Anal. Machine Intell., vol. 8, no. 6, pp. 679–698, Nov. 1986
15. A. Califano, “Feature recognition using correlated information contained in multiple neighborhoods,” in Proc. 7th Nat. Conf. Artificial Intelligence, July 1988, pp. 831–836.
16. R. M. Bolle and R. W. Taylor, “Generalized neighborhoods: A new approach to feature extraction,” in Proc IEEE Conf. Computer Vision and Pattern Recognition, June 1989.
17. A. Califano and R. Mohan, “Generalized shape autocorrelation,” in Proc. AAAI-90, July 1990, pp. 1067–1073.
18. A. Califano and R. Mohan, “Multidimensional indexing for recognizing visual shapes,” in Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 1991, pp. 28–34.
19. I. Chakravarty and H. Freeman, “Characteristic view as a basis for three-dimensional dimensional object recognition,” in Proc. SPIE Conf. Robot Vision, 1982, pp. 37–45.
20. R. T. Chen and C. R. Dyer, “Model-based recognition in robot vision,” ACM Comput. Surveys, vol. 18, no. 1, pp. 66–108, Mar. 1986.
21. D. T. Clemens and D. W. Jacobs, “Model group indexing for recognition,” in Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 1991, pp. 4–9.
22. R. O. Duda and P. E. Hart, “Use of the Hough transform to detect lines and curves in images,” Common. ACM, vol. 15, no. 1, pp. 11-15, 1972.
23. G. J. Ettinger, “Large hierarchical object recognition using libraries of parameterized model sub-parts,” in Proc. IEEE Conf. Computer Vision and Pattern Recognition, June 1988, pp. 32–41.
24. O. D. Faugeras and M. Hebert, “A 3D recognition and positioning algorithm using geometric matching between primitive surfaces,” in Proc. 8th Int. Joint Conf. Artificial Intelligence, Aug. 1983, pp. 996–1002.
25. J. A. Feldman and D. H. Ballard, “Connectionist models and their properties,” Cognitive Sci., vol. 6, 1981, pp. 205–254.
26. W. E. L. Grimson and T. Lozano-Perez, “Model-based recognition and localization from sparse range data or tactile data,” Int. J. Robotics Research, vol. 3, no. 3, pp. 3–34, Fall 1984.
27. Z. Gigus and J. Malik, “Computing the aspect graph for line drawings of polyhedral objects,” IEEE Trans. Pattern Anal. and Machine Intell., vol. 12, no. 2, Feb. 1990.
28. C. Goad, “Special purpose automatic programming for 3D model-based vision,” in Proc. DARPA Image Understanding Workshop, 1983, pp. 94–104.
29. W. E. L. Grimson, “The combinatorics of heuristic search termination for object recognition in cluttered environments,” Massachusetts Institute of Technology, Cambridge, MIT Al Memo 1111, May 1989.
30. W. E. L. Grimson and D. P. Huttenlocher, “On the sensitivity of geometric hashing,” in Proc. 3rd Int. Conf. Computer Vision, Osaka, Japan, 1990
31. C. Hansen and T. Henderson, “CAGD-based computer vision,” in Proc. Workshop on Computer Vision, Nov.-Dec. 1987, pp. 100–105.
32. G. Hinton and J. Andreson, Parallel Models of Associative Memory: Lawrence Erlbaum, 1981
33. P. Horaud and R. C. Bolles, “3D PO's strategy for matching three-dimensional dimensional objects in range data,” in Proc. IEEE 1984 Int. Conf. Robotics, Mar. 1984, 78–85.
34. P. V. C. Hough, “Methods and means for recognizing complex patterns,” U. S. Patent 3069654, 1962.
35. D. P. Huttenlocher and S. Ullman, “Object recognition using alignment,” in Proc. 1st. Int. Conf. Computer Vision, pp. 102-111, 1987.
36. D. P. Huttenlocher, “Three-dimensional recognition of solid objects from a two-dimensional image,” Ph.D. dissertation, Massachusetts Institute of Technology, Cambridge, MIT AI-Lab. Tech. Rep. # 1045, 1988.
37. K. Ikeuchi and T. Kanade, “Automatic generation of object recognition programs,” IEEE Proc., vol. 76, no. 8, Aug. 1988, pp. 1016–1035.
38. A. Kalvin, E. Schonberg, J. T. Schwartz, and M. Sharir, “Two-dimensional, dimensional, model-based, boundary matching using footprints,” Int. J. Robotics Research, vol. 6, no. 4, Winter 1986.
39. J. Koenderink and A. van Doom, “The internal representation of solid shape with respect to vision,” Biological Cybern., vol. 32, pp. 211–216, 1979.
40. Y. Lamdan, J. T. Schwartz, and H. J. Wolfson, “On recognition of 3D object from 2D images,” in Proc. IEEE Conf Robotics and Automation, pp. 1407–1413.
41. Y. Lamdan, J. T. Schwartz, and H. J. Wolfson, “Object recognition by affine invariant matching,” in Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 335–344.
42. Y. Lamdan and H. J. Wolfson, “Geometric hashing: A general and efficient model-based recognition scheme,” in Proc. 2nd Int. Conf. Computer Vision, Dec. 1988.
43. Y. Lamdan and H. J. Wolfson, “On the error analysis of geometric hashing,” Robotics Lab, New York University, Tech. Rep. 213. Oct. 1989.
44. D. G. Lowe, “The viewpoint consistency constraint,” Int. J. Comput. Vision, vol. 1, 1987, pp. 57–72.
45. R. Mohan and R. Nevatia, “Perceptual organization for scene segmentation and description,” in IEEE Trans. Pattern Anal. and Machine Intell., vol. 14, no. 6, June 1992, pp. 616–635.
46. J. L. Mundy and A. J. Heller, “The evolution and testing of a model-based based object recognition system,” in Proc. 3rd. Int. Conf. Computer Vision, pp. 268–282, 1990.
47. R. Nevatia and T. O. Binford, “Description and recognition of curved objects,” Artificial Intell., vol. 8, no. 1, pp. 77–98, 1977.
48. Suggested by one of the referees, during the review process.
49. I. Rigoutsos and R. Hummel, “On a scalable parallel implementation of geometric hashing on the connection machine,” Courant Inst. of Math. Science, New York Univ., Tech. Rep. 554, Apr. 1991.
50. I. Rigoutsos and R. Hummel, “Robust similarity invariant matching in the presence of noise,” in Proc. 8th. Israeli Conf. Artificial Intelligence and Computer Vision, Dec., 1991.
51. A. Rosenfeld and A. C. Kak, Digital Picture Processing. New York: Academic, 1982.
52. D. E. Rumelhart and McClelland, Eds., Parallel Distributed Processing: Exploratioms in the Microsructures of Computing. Cambridge, MA: MIT Press, 1986.
53. D. Sabbah, “Computing with connections in visual recognition of origami objects,” Cognitive Sci., vol. 9, no. 1, Jan. Mar. 1985, pp. 25–50.
54. R. Shapira and H. Freeman, “Reconstruction of curved surface bodies from a set of imperfect projections,” in Proc. 5th Int. Joint Conf. Artificial Intelligence, Aug. 1977, pp. 22–26.
55. F. Stein and G. Medioni, “Efficient two dimensional object recognition,” in Proc. Int. Conf Pattern Recognition, Alantic City, NJ, June 1990.
56. G. Taubin, “Nonplanar curve and surface estimation in 3 space,” in Proc. IEEE Conf. on Robotics and Automation, Apr. 1988.
57. J. L. Turney, T. N. Mudge, and R. A. Volz, “Recognizing partially occluded parts,” IEEE Trans. Pattern Anal. Machine Intell., vol. 7, no. 4, pp. 410–421, July 1985.
58. I. Weiss, “Projective invariants of shapes,” in Proc. DARPA Image Understanding Workshop, pp. 1125–1134, Apr. 1988.