3D object recognition and pose with relational indexing

Computer Vision and Image Understanding

Volumn 79, Issue 3, 2000, Pages 364-407

  Costa, Mauro S ^a   Shapiro, Linda G ^b  

^a BOEING COMPANY   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE EXTRACTION; MATHEMATICAL MODELS; OBJECT RECOGNITION;

LINEAR POSE ESTIMATION; RELATIONAL INDEXING;

COMPUTER VISION;

EID: 0034275842     PISSN: 10773142     EISSN: None     Source Type: Journal    
DOI: 10.1006/cviu.2000.0865     Document Type: Article

References (59)

1. J. Ben-Arie and A. Z. Meiri, 3-d object recognition by optimal matching search of multinary relations, Comput. Vision Graphics Image Process. 37, 1987, 345-361.
2. R. Bergevin and M. D. Levine, Generic object recognition: Building and matching coarse descriptions from line drawings, IEEE Trans. Pattern Anal. Mach. Intell. 15, 1993, 19-36.
3. J. P. Besl and R. C. Jain, Three-dimensional object recognition, ACM Comput. Surveys 17, 1985, 75-154.
4. R. C. Bolles and R. A. Cain, Recognizing and locating partially visible objects: The local-feature-focus method, Int. J. Robotics Res. 1(3), 1982, 57-82.
5. R. C. Bolles and P. Horaud, 3dpo: A three-dimensional part orientation system, Int. J. Robotics Res. 5(3), 1986, 3-26.
6. J. P. Brady, N. Nandhakumar, and J. K. Aggarwal, Recent progress in object recognition from range data, Image Vision Comput. 7(4), 1989, 295-307.
7. J. B. Burns and E. M Riseman, Matching complex images to multiple 3d objects using view description networks, in Proc. of the IEEE CVPR, pp. 328-334, 1992.
8. A. Califano and R. Mohan, Multidimensional indexing for recognition of visual shapes, IEEE Trans. Pattern Anal. Mach. Intell. 16, 1994, 373-482.
9. O. I. Camps, L. G. Shapiro, and R. M. Haralick, Image prediction for computer vision, in Three-dimensional Object Recognition Systems (A. Jain and P. Flynn, Eds.), Elsevier, Amsterdam/New York, 1993.
10. C. H. Chen and A. C. Kak, A robot vision system for recognizing 3d objects in lower order polynomial time, IEEE Trans. Systems Man Cybernetics 19, 1989, 1535-1563.
11. C. H. Chen and P. Mulgaonkar, Automatic vision programming, CVGIP: Image Understanding 55, 1992, 170-183.
12. J. L. Chen and G. C. Stockman, Matching curved 3d object models to 2d images, in Second CAD-Based Vision Workshop (A. Kak and K. Ikeuchi, Eds.), pp. 210-227, 1994.
13. R. T. Chin and C. R. Dyer, Model-based recognition in robot vision, ACM Comput. Surveys 18, 1986, 67-108.
14. Y. Chou and L. G. Shapiro, Probabilistic relational indexing, in Proceedings of the International Conference on Pattern Recognition, Brisbane, Australia, 1997, pp. 1331-1335, 1998.
15. M. S. Costa, R. M. Haralick, and L. G. Shapiro, Optimal affine invariant point matching, in Proceedings of 10th ICPR, Vol. 1, pp. 233-236, 1990.
16. M. S. Costa and L. G. Shapiro, Scene analysis using appearance-based models and relational indexing, in International Symposium on Computer Vision, November 1995, pp. 103-108.
17. M. S. Costa, Object Recognition and Pose Estimation Using Appearance-Based Features and Relational Indexing, Ph.D. Dissertation, Department of Electrical Engineering, University of Washington, 1997.
18. M.-P. Dubuisson and A. K. Jain, A modified Hausdorff distance for object matching, in Proceedings of the 12th International Conference on Pattern Recognition, Jerusalem, Israel, 1994.
19. W. H. Press et al., Numerical Recipes in C, Cambridge Univ. Press, Cambridge, UK, 1992.
20. D. Forsyth et al., Invariant descriptors for 3-d object recognition and pose, IEEE Trans. Pattern Anal. Mach. Intell. 13, 1991, 971-991.
21. M. Dhome et al., Spatial localization of modeled objects of revolution in monocular perspective vision, in First European Conference on Computer Vision, 1989.
22. C. Dorai and A. K. Jain, Shape spectrum based view grouping and matching of 3D free-form objects, IEEE Trans. Pattern Anal. Mach. Intell. 19, 1997, 1131-1138.
23. A. Etemadi, Robust segmentation of edge data, in Proceedings of the IEE Image Processing Conference, 1992.
24. T. J. Fan, G. Medioni, and R. Nevatia, Recognizing 3d objects using surface descriptions, IEEE Trans. Patt. Anal. Mach. Intell. 11, 1989, 1140-1157.
25. O. D. Faugeras, Three-Dimensional Computer Vision, a Geometric Viewpoint, MIT Press, Cambridge, MA, 1993.
26. O. D. Faugeras and M. Hebert, The representation, recognition, and locating of 3d objects, Int. J. Robotics Res. 5(3), 1986, 27-52.
27. P. J. Flynn and A. K. Jain, Bonsai: 3d object recognition using constrained search, IEEE Trans. Pattern Anal. Mach. Intell. 13, 1991, 1066-1075.
28. S. Ganapathy, Decomposition of transformation matrices for robot vision, in Proceedings of the International Conference on Robotics and Automation, 1984.
29. C. Goad, Fast 3D model-based vision, in From Pixels to Predicates (A. P. Pentland, Ed.), pp. 371-391, 1986.
30. K. D. Gremban and K. Ikeuchi, Appearance-based vision and the automatic generation of object recognition programs, in Three-dimensional Object Recognition Systems (A. Jain and P. Flynn, eds.), Elsevier, Amsterdam/New York, 1993.
31. L. Grewe and A. Kak, Interactive learning of multiple attribute hash table for fast 3d object recognition, in Proceedings of the Second CAD-Based Vision Workshop, February 1994, pp. 124-131.
32. R. M. haralick, C. N. Lee, K. Ottenburg, and M. Nolle, Review and analysis of the three-point perspective pose estimation problem, Int. J. Comput. Vision 13, 1994, 331-356.
33. R. M. Haralick and L. G. Shapiro, Computer and Robot Vision, Addison-Wesley, Reading, MA, 1993.
34. I. Higuchi, H. Delingette, M. Hebert, and K. Ikeuchi, Merging multiple views using a spherical representation, in Proceedings of the Second CAD-Based Vision Workshop, February 1994, pp. 124-131.
35. D. P. Huttenlocher, Three-Dimensional Recognition of Solid Objects from a Two-Dimensional Image, Ph.D. dissertation, Massachusetts Institute of Technology, 1988.
36. D. P. Huttenlocher and S. Ullman, Recognizing solid objects by alignment with an image, Int. J. Comput. Vision 5, 1990, 195-212.
37. K. Ikeuchi and T. Kanade, Towards automatic generation of object recognition programs, CVGIP: Image Understanding 76, 1988, 1016-1035.
38. A. K. Jain and R. Hoffman, Evidence-based recognition of 3-d objects, IEEE Trans. Pattern Anal. Mach. Intell. 10, 1988, 783-802.
39. Q. Ji, M. S. Costa, R. M. Haralick, and L. G. Shapiro, An integrated technique for pose estimation from different geometric features, in Proceedings of Vision Interface '98, Vancouver, June 18-20, 1998, pp. 77-84.
40. A. E. Johnson and M. Hebert, Efficient multiple model recognition in cluttered 3-D scenes, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1998, pp. 671-677.
41. Y. Lamdan and H. J. Wolfson, Geometric hashing: A general and efficient model-based recognition scheme, in Second International Conference on Computer Vision, pp. 238-249, 1988.
42. D. G. Lowe, Three-dimensional object recognition from single two-dimensional images, Artificial Intell. 31, 1987, 355-395.
43. H. Murase and S. K. Nayar, Visual learning of object models from appearance, Int. J. Comput. Vision 14(1), 1995, 5-24. [Also Technical Report CUCS-054-92]
44. C. F. Olson, Probabilistic indexing for object recognition, IEEE Trans. Pattern Anal. Mach. Intell. 17, 1995, 518-522.
45. T. Q. Phong, R. Horaud, A. Yassine, and P. D. Tao, Objet pose from 2-d to 3-d point and line correspondences, Int. J. Comput. Vision 15, 1995, 225-243.
46. A. R. Pope, Model-based Object Recognition - A Survey of Recent Research, Technical Report 94-04, January 1994.
47. K. Pulli, Triplet-based object recognition using synthetic and real probability models, in Proceedings of ICPR96, 1996, Vol. IV, pp. 75-79.
48. M. Seibert and A. M. Waxman, Adaptive 3d object recognition from multiple views, IEEE Trans. Pattern Anal. Mach. Intell. 14, 1992, 107-124.
49. L. G. Shapiro and R. M. Haralick, A metric for comparing relational descriptions, IEEE Trans. Pattern Anal. Mach. Intell. 7, 1985, 90-94.
50. F. Stein and G. Medioni, Structural indexing: Efficient three dimensional object recognition, IEEE Trans. Pattern Anal. Mach. Intell. 14, 1992, 125-145.
51. G. Stockman, Object recognition and localization via pose clustering, Comput. Vision Graphics Image Process. 40, 1987, 361-387.
52. T. M. Strat and M. A. Fishler, Contex-based vision: recognizing objects using information from both 2d and 3d imagery, IEEE Trans. Pattern Anal. Mach. Intell. 13, 1991, 1050-1065.
53. P. Suetens, P. Fua, and A. J. Hanson, Computational strategies for object recognition, ACM Comput. Surveys 24, 1992, 5-61.
54. K. B. Thornton, Clustering Similar Views of an Object Using a Relational Distance Approach, Master's thesis, 1989.
55. R. Y. Tsai, An efficient and accurate camera calibration technique for 3d machine vision, IEEE J. Robotics Automation 3(4), 1987, 323-344.
56. R. C. Bolles and P. Horaud, 3DPO: a three-dimensional part orientation system, Int. J. Robotics Res. 5(3), 1986, 3-26.
57. L. B. Wolff, Polarization-based material classification from specular reflection, IEEE Trans. Pattern Anal. Mach. Intell. 12, 1990, 1059-1071.
58. A. K. C. Wong, L. Rong, and X. Liang, Robotic vision: 3D object recognition and pose determination, in Proceedings of the 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1202-1209, 1998.
59. S. Zhang, G. D. Sullivan, and K. D. Baker, The automatic construction of a view-independent relational model for 3d object recognition, IEEE Trans. Pattern Anal. Mach. Intell. 15, 1993, 531-544.