A survey of motion-parallax-based 3-D reconstruction algorithms

IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews

Volumn 34, Issue 4, 2004, Pages 532-548

  Lu, Ye ^a   Zhang, Jason Z ^b   Wu, Q M Jonathan ^b   Li, Ze Nian ^a  

^a SIMON FRASER UNIVERSITY   (Canada)

^b NATIONAL RESEARCH COUNCIL CANADA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CALIBRATION; CAMERAS; CONSTRAINT THEORY; FEATURE EXTRACTION; IMAGE RECONSTRUCTION; MATRIX ALGEBRA; MOTION ESTIMATION; OBJECT RECOGNITION; THREE DIMENSIONAL COMPUTER GRAPHICS;

CAMERA SELF CALIBRATION; MOTION PARALLAX; THREE DIMENSIONAL RECONSTRUCTION;

COMPUTER VISION;

EID: 7744219654     PISSN: 10946977     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCC.2004.829300     Document Type: Article

References (80)

1. D. Marr, [i Vision i]. New York: W. H. Freeman, 1982.
2. E. Adelson and J. Bergen, "The plenoptic fucntion and the elements of early vision," in [i Computational Models of Visual Processing i], M. Landy and J. A. Movshon, Eds. Cambridge, MA: MIT Press, 1991, pp. 3-20.
3. S. Baker, T. Sim, and T. Kanade, "When is the shape of a scene unique given its lightfield: A fundamental theorem of 3D vision?," [i IEEE Trans. Pattern Anal. Machine Intell. i], vol. 25, pp. 100-109, Jan. 2003.
4. R. Hartley and A. Zisserman, [i Multiple View Geometry in Computer Vision. i] Cambridge, U.K.: Cambridge Univ. Press, 2000.
5. O. Faugeras, Q. T. Luong, and T. Papadopoulo, [i The Geometry of Multiple Images: i] MIT Press, 2001.
6. R. I. Hartley, "In defense of the eight-point algorithm," [b IEEE Trans. Pattern Anal. Machine Intell. b], vol. 19, pp. 580-593, Oct. 1997.
7. R. Tsai, "A versatile camera calibration technique for high accuracy 3D machine vision metrology using off the shelf TV cameras and lenses," [i IEEE J. Robot. Automat. i], vol. RA-3, no. 4, pp. 323-344, 1987.
8. Z. Zhang, "A flexible new technique for camera calibration," [i IEEE Trans. Pattern Anal. Machine Intell. i], vol. 22, pp. 1330-1334, Nov. 2000.
9. J.-Y. Bouguet. (2004) Camera Calibration Toolbox for Matlab. [Online]. Available: http://www.vision.caltech.edu/bouguet/calibc/
10. Intel Corporation. (2004) Intel Open Source Computer Vision Library. [Online]. Available: http://www.intel.com/research/mrl/research/opencv/
11. D. D. Morris, K. Kanatani, and T. Kanade, "Gauge fixing for accurate 3D estimation," in [i Proc. IEEE Conf. Computer Vision and Pattern Recognition i], 2001, pp. 343-350.
12. R. Hartley and P. Sturm, "Triangulation," [i Comput. Vis. Image Understanding i], vol. 68, no. 2, pp. 146-157, 1997.
13. H. P. Moravec, "Toward automatic visual obstacle avoidance," in [i Proc. Int. Joint Conf. Artificial Intelligence i], 1977, pp. 584-584.
14. H. P. Moravec, "Visual mapping by a robot rover," in [i Proc. 6th Int. Joint Conf. Artificial Intelligence i], 1977, pp. 598-600.
15. C. G. Harris and M. Stephens, "A combined corner and edge detector," in [i Proc. 4th Alvey Vision Conf. i], 1988, pp. 147-151.
16. P. R. Beaudet, "Rotational invariant image operator," in [i Proc. Int. Conf. Pattern Recognition i], 1978, pp. 579-583.
17. L. Kitchen and A. Rosenfeld, "Gray-level corner detection," [i Pattern Recognit. Lett. i], pp. 95-102, 1982.
18. L. Dreschler and H. H. Nagel, "Volumetric model and 3D trajectory of a moving car derived from monocular tv-frame sequence of a street scene," [i Comput. Vis., Graph., Image Processing i], vol. 20, no. 3, pp. 199-228, 1981.
19. H. H. Nagel, "Principles of (low level) computer vision," in [i Fundamentals in Computer Understanding: Speech and Vision i], J. P. Haton, Ed. Cambridge, UX.: Cambridge Univ. Press, 1987, pp. 113-139.
20. O. A. Zuniga and R. M. Haralick, "Corner detection using the facet model," in [i Proc. IEEE Conf. Computer Vision and Pattern Recognition i], 1983, pp. 30-37.
21. S. M. Smith and J. M. Brady, "Susan - A new approach to low level image processing," [i Int. J. Comput. Vis. i], vol. 23, no. 1, pp. 45-78, 1997.
22. F. Mokhtarian and R. Suomela, "Robust image corner detection through curvature scale space," [i IEEE Trans. Pattern Anal. Machine Intell. i], vol. 20, pp. 1376-1381, Dec. 1998.
23. C. Tomasi and T. Kanade, "Detection and tracking of point features,", Tech. Rep. CMU-CS-91-132, 1991.
24. Z. Zhang, R. Deriche, O. Faugeras, and Q.-T. Luong, "A robust technique for matching two uncalibrated images through the recovery of unknown epipolar geometry" [i Artific. Intell. J. i], vol. 78, pp. 87-119, 1995.
25. D. Marr and T. Poggio, "Cooperative computation of stereo disparity," [i Science i], vol. 194, pp. 283-287, 1976.
26. M. Pilu, "A direct method for stereo correspondence based on singular value decomposition," in [i Proc. Int. Conf. Computer Vision and Pattern Recognition i], San Juan, Puerto Rico, 1997, pp. 261-266.
27. H. H. Baker and T. O. Binford, "Depth from edge and intensity based stereo," in [i Proc. 7th Int. Joint Conf. Artificial Intelligence i], 1981, pp. 631-636.
28. Y. Ohta and T. Kanade, "Stereo by intra- and inter-scanline search using dynamic programming," [i IEEE Trans. Pattern Anal. Machine Intell. i], vol. PAMI-7, pp. 139-145, Feb. 1985.
29. Z. N. Li, "Stereo correspondence based on line matching in Hough space using dynamic programming," [i IEEE Trans. Syst., Man, Cybern. i], vol. 24, pp. 144-152, 1994.
30. J. L. Barron, D. J. Fleet, and S. S. Beuchemein, "Performance of optical flow techniques," [i Int. J. Comput. Vis. i], vol. 12, no. 1, pp. 43-77, 1994.
31. D. J. Heeger and A. D. Jepson, "Subspace methods for recovering rigid motion i: Algorithm and implementation," [i Int. J. Comput. Vis. i], vol. 7, no. 2, pp. 95-117, 1992.
32. M. Zucchelli, "Optical flow based structure from motion," Ph.D. thesis, Royal Institute of Technology, 2002.
33. O. Faugeras, [i Three-Dimensional Computer Vision: A Geometric Viewpoint i]. Cambridge, MA: MIT Press, 1993.
34. S. Z. Li, [i Markov Random Field Modeling in Computer Vision i]. New York: Springer, 1995.
35. V. Kolmogorov and R. Zabih, "Computing visual correspondence with occlusions using graph cuts," in [i Proc. Int. Conf. Computer Vision i], Vancouver, BC, Canada, 2001, pp. 508-515.
36. Y. Boykov and V. Kolmogorov, "An experimental comparison of min-cut/max-flow algorithms for energy minimization in computer vision," in [i Proc. 3rd Int. Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition i], Sophie Antipolis, France, 2001, pp. 359-374.
37. V. Kolmogorov and R. Zabih, "What energy functions can be minimized via graph cuts?," in [i Proc. European Conf. Computer Vision i], vol. III, Copenhagen, Denmark, 2002, pp. 65-82.
38. D. Greig, B. Porteous, and A. Seheult, "Exact maximum a posterior estimation for binary images," [i J. Roy. Statist. Soc. i], vol. 51, no. 2, pp. 271-279,1989.
39. D. Scharstein and R. Szeliski, "A taxonomy and evaluation of dense two-frame stereo correspondence algorithms," [i Int. J. Comput. Vis. i], vol. 47, no. 1-3, pp. 7-42, 2002.
40. V. Kolmogorov and R. Zabih, "Multi-camera scene reconstruction via graph cuts," in [i Proc. European Conf. Computer Vision i], 2002.
41. G. Slabaugh, B. Culbertson, T. Malzbender, and R. Schafer, "A survey of methods for volumetric scene reconstruction from photographs," in [i Int. Workshop Volume Graphics i], Stony Brook, NY, 2001.
42. W. Martin and J. K. Aggarwal, "Volumetric description of objects from multiple views," [i IEEE Trans. Pattern Anal. Machine Intell. i], vol. PAMI-5, pp. 150-158, Feb. 1983.
43. C. H. Chien and J. K. Aggarwal, "A volume/surface representation," in [i Proc. Int. Conf. Pattern Recognition i], 1984.
44. C. H. Chien and J. K. Aggarwal, "Volume/surface octrees for the representation of three dimensional objects," [i Comput. Vis., Graph., Image Process. i], vol. 36, no. 1, pp. 100-113, 1986.
45. M. Potmesil, "Generating octree models of 3D objects from their silhouettes in a sequence of images," [i Comput. Vis., Graph., Image Process. i], vol. 40, no. 1, pp. 1-29, 1987.
46. R. Szeliski, "Rapid octree representation from image sequences," [i Comput. Vis., Graph., Image Process. i], vol. 58, no. 1, pp. 23-32, 1993.
47. D. Snow, P. Viola, and R. Zabih, "Exact voxel occupancy with graph cuts," in [i Proc. IEEE Conf. Computer Vision and Pattern Recognition i], 2000.
48. S. Seitz and C. Dyer, "Photorealistic scene reconstruction by voxel coloring," in [i Proc. IEEE Conf. Computer Vision and Pattern Recognition i], San Juan, Puerto Rico, 1997, pp. 1067-1073.
49. S. Seitz, "Photorealistic scene reconstruction by voxel coloring," [i Int. J. Comput. Vis. i], vol. 35, no. 2, pp. 151-173, 1999.
50. A. Prock and C. Dyer, "Toward real-time voxel coloring," in [i Proc. DARPA Image Understanding Workshop i], Monterrey, CA, 1998, pp. 315-321.
51. W. B. Culbertson, T. Malzbender, and G. Slabaugh, "Generalized voxel coloring," in [i Proc. ICCV Workshop, Vision Algorithms Theory and Practice i], Corfu, Greece, 1999, pp. 67-74.
52. O. Faugeras and R. Keriven, "Variational principles, surface evolution, PDE's, level set methods, and the stereo problem," [i IEEE Trans. Image Processing i], vol. 7, pp. 336-344, 1998.
53. L. Robert and R. Deriche, "Dense depth map reconstruction: A minimization and regularization approach which perserves discontinuities," in [i Proc. European Conf. Computer Vision i], Cambridge, U.K., 1996, pp. 439-451.
54. L. Robert, R. Deriche, and O. Faugeras, "Dense depth recovery from stereo images," in [i Proc. European Conf. Artificial Intelligence i], Vienna, Austria, 1992, pp. 821-823.
55. H. Jin, S. Soatto, and A. J. Yezzi, "Variational multiframe stereo in the presence of specular reflections," in [i Proc. 1st Int. Symp. 3D Data Processing Visualization and Transmission i], Padova, Italy, 2002, pp. 626-630.
56. H. Jin, S. Soatto, and A. J. Yezzi, "Multi-view stereo beyond lambert," in [i Proc. IEEE Conf. Computer Vision and Pattern Recognition i], Madison, WI, 2002, pp. 171-179.
57. Q. T. Luong and T. Vieville, "Canonical representations for the geometries of multiple projective views," [i Comput. Vis. Image Understanding i], vol. 64, no. 2, pp. 193-229, Sept. 1996.
58. C. Tomasi and T. Kanade, "Shape and motion from image streams under orthography: A factorization approach," [i Int. J. Comput. Vis. i], vol. 9, no. 2, pp. 137-154, Nov. 1992.
59. P. Sturm and W. Triggs, "A factorization based algorithm for multi-image projective structure and motion," in [i Proc. European Conf. Computer Vision i], 1996, pp. 709-720.
60. B. Caprile and V. Torre, "Using vanishing points for camera calibration," [i Int. J. Comput. Vis. i], vol. 4, no. 2, pp. 127-139, 1986.
61. S. T. Barnard, "Interpreting perspective images," [i Artificial Intelligence i], vol. 21, pp. 435-462, 1983.
62. L. Quan and R. Mohr, "Determining perspective structures using hierarchical bough transform," [i Pattern Recognit. Lett. i], vol. 9, pp. 279-286, 1989.
63. E. Lutton, H. Maitre, and J. Lopez-Krahe, "Contribution to the determination of vanishing points using Hough transform," [i IEEE Trans. Pattern Anal. Machine Intell. i], vol. 16, pp. 430-438, Sept. 1994.
64. M. J. Magee and J. K. Aggarwal, "Determining vanishing points from perspective images," [i Comput. Vis., Graph., Image Process. i], vol. 26, pp. 256-267, Sept. 1984.
65. C. Rother, "A new approach for vanishing point detection in architectural environments," in [i Proc. British Machine Vision Conf. i], Bristol, U.K., 2000, pp. 382-391.
66. F. A. van den Heuvel, "Vanishing point detection for architectural photogrammetry," [i Int. Arch. Photogramm. Remote Sensing i], vol. XXXII, no. 5, 1998.
67. D. Liebowitz and A. Zisserman, "Combining scene and auto-calibration constraints," in [i Proc. Int. Conf. Computer Vision i], Corfu, Greece, 1999, pp. 293-300.
68. W. Triggs, "Auto-calibration and the absolute quadric," in [i Proc. IEEE Conf. Computer Vision and Pattern Recognition i], 1997, pp. 609-614.
69. O. D. Faugeras and Q. T. Luong, "Camera self-calibration: Theory and experiments," in [i Computer Vision - ECCV '92 i], ser. LNCS-Series. New York: Springer-Verlag, 1992, vol. 588, pp. 321-334
70. S. J. Maybank and O. D. Faugeras, "A theory of self-calibration of a moving camera," [i Int. J. Comput. Vis. i], vol. 8, no. 2, pp. 123-151, 1992.
71. T. Vièville and D. Lingrand, "Using singular displacements for uncalibrated monocular vision systems," INRIA, Tech. Rep. 2678, 1995.
72. R. I. Hartley, "Kruppa's equations derived from the fundamental matrix," [i IEEE Trans. Pattern Anal. Machine Intell. i], vol. 19, pp. 133-135, Feb. 1997.
73. P. Sturm, "A case against Kruppa's equations for camera self-calibration," [i IEEE Trans. Pattern Anal. Machine Intell. i], vol. 22, pp. 1199-1204, Oct. 2000.
74. M. Pollefeys and L. van Gool, "Stratified self-calibration with the modulus constraint," [i IEEE Trans. Pattern Anal. Machine Intell. i], vol, 21, pp. 707-724, Aug. 1999.
75. B. K. P. Horn, "Motion field are hardly ambiguous," [i Int. J. Comput. Vis. i], pp. 259-274, 1987.
76. P. Sturm, "Critical motion sequences for monocular self-calibration and uncalibrated euclidean reconstruction," in [i Proc. IEEE Int. Conf. Computer Vision and Pattern Recognition i], 1997, pp. 1100-1105.
77. M. Armstrong, A. Zisserman, and R. Hartley, "Self-calibration from image triplets," in [i Proc. European Conf. Computer Vision i], 1996, pp. 3-16.
78. R. I. Hartley, "Self-calibration from multiple views with a rotating camera," in [i Proc. European Conf. Computer Vision i], 1994, pp. 471-478.
79. C. Wiles and M. Brady, "Ground plane motion camera models," in [i Proc. European Conf. Computer Vision i], 1996, pp. 238-247.
80. T. Moons, L. van Gool, M. van Diest, and E. Pauwels, "Affine reconstruction from perspective image pairs," in [i Darpa-Esprit Workshop on Applications of Invariants in Computer Vision i], 1993, pp.