A review on egomotion by means of differential epipolar geometry applied to the movement of a mobile robot

Pattern Recognition

Volumn 36, Issue 12, 2003, Pages 2927-2944

  Armangué, Xavier ^a   Araújo, Helder ^b   Salvi, Joaquim ^a  

^a UNIVERSITY OF GIRONA   (Spain)

^b UNIVERSITY OF COIMBRA   (Portugal)

Author keywords

Computer vision; Differential epipolar constraint; Egomotion; Optical flow

Indexed keywords

ALGORITHMS; COMPUTER VISION; MOBILE ROBOTS; MOTION ESTIMATION;

SELF-CALIBRATED STEREOSCOPIC SYSTEMS;

PATTERN RECOGNITION;

COMPUTER VISION;

EID: 0142088846     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(03)00183-3     Document Type: Article

References (48)

1. Hall E.L. Tio J.B.K. McPherson C.A. Sadjadi F.A. Measuring curved surfaces for robot vision Comput. J. 15 12 1982 42-54
2. O.D. Faugeras, G. Toscani, The calibration problem for stereo, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Los Alamitos, CA, 1986, pp. 15-20.
3. Salvi J. Batlle J. Mouaddib E.M. A robust-coded pattern projection for dynamic 3D scene measurement Pattern Recognition Lett. 19 11 1998 1055-1065
4. Tsai R.Y. A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses IEEE Int. J. Robotics Automat. RA-3 4 1987 323-344
5. Weng J. Cohen P. Herniou M. Camera calibration with distortion models and accuracy evaluation IEEE Trans. Pattern Anal. Mach. Intell. 14 10 1992 965-980
6. Salvi J. Armangué X. Batlle J. A comparative review of camera calibrating methods with accuracy evaluation Pattern Recognition 35 7 2002 1617-1635
7. Hartley R.I. Kruppa's equations derived from the fundamental matrix Pattern Anal. Mach. Intell. 19 2 1997 133-135
8. Longuet-Higgins H.C. A computer algorithm for reconstructing a scene from two projections Nature 293 1981 133-135
9. Huang T.S. Faugeras O.D. Some properties of the E matrix in two-view motion estimation IEEE Trans. Pattern Anal. Mach. Intell. 11 12 1989 1310-1312
10. Faugeras O.D. Three-Dimensional Computer Vision 1993 The MIT Press Cambridge, MA
11. Zhang Z. Determining the epipolar geometry and its uncertainty: A review Int. J. Comput. Vision 27 2 1998 161-198
12. Luong Q.-T. Faugeras O.D. The fundamental matrix: Theory, algorithms, and stability analysis Int. J. Comput. Vision 17 1 1996 43-75
13. Torr P.H.S. Murray D.W. The development and comparison of robust methods for estimating the fundamental matrix Int. J. Comput. Vision 24 3 1997 271-300
14. Armangué X. Salvi J. Overall view regarding fundamental matrix estimation Image Vision Comput. 21 2 2003 205-220
15. R.M. Haralick, L.G. Shapiro, Computer and Robot Vision, Vol. 2, Addison-Wesley Publishing Company, Reading, MA, 1992.
16. Viéville T. Faugeras O.D. The first order expansion of motion equations in the uncalibrated case Comput. Vision Graphics Image Process.: Image Understanding 64 1 1996 128-146
17. Brooks M.J. Chojnacki W. Baumela L. Determining the ego-motion of an uncalibrated camera from instantaneous optical flow J. Opt. Soc. Am. 10 1997 2670-2677
18. Ma Y. Košecká J. Sastry S. Linear differential algorithm for motion recovery: a geometric approach Int. J. Comput. Vision 36 1 2000 71-89
19. Trucco E. Verri A. Introductory Techniques for 3D Computer Vision 1998 Prentice-Hall, Inc. Englewood Cliffs, NJ
20. J. Barron, D. Fleet, S. Beauchemin, T. Burkitt, Performance of optical flow techniques, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Champaigne, IL, USA, 1992, pp. 236-242.
21. X. Zhuang, R.M. Haralick, Rigid body motion on optical flow image, in: Proceedings of the First International Conference on Artificial Intelligence Applications, Denver, CO, 1984, pp. 366-375.
22. Zhuang X. Huang T.S. Ahuja N. Haralick R.M. A simplified linear optic flow-motion algorithm Comput. Vision Graphics Image Process. 42 1988 334-344
23. Tsai R.Y. Huang T.S. Uniqueness and estimation of three-dimensional motion parameters of rigid objects with curved surfaces IEEE Trans. Pattern Anal. Mach. Intell. 6 1 1984 13-27
24. Hegger D.J. Jepson A.D. Subspace methods for recovering rigid motion I: Algorithm and implementation Int. J. Comput. Vision 7 2 1992 95-318
25. A.D. Jepson, D.J. Heeger, A fast subspace algorithm for recovering rigid motion, in: Proceedings of the IEEE Workshop on Visual Motion, Princeton, NJ, 1991, pp. 124-131.
26. A.D. Jepson, D.J. Heeger, Linear subspace methods for recovering translation direction, in: L. Harris, M. Jenkin (Eds.), Spatial Vision in Humans and Robots, Cambridge University Press (1993) 39-62.
27. G. Toscani, O.D. Faugeras, Structure and motion from two noisy perspective images, in: Proceedings of the IEEE Conference on Robotics and Automation, San Francisco, CA, 1986, pp. 221-227.
28. Kanatani K. Unbiased estimation and statistical analysis of 3-D rigid form two views IEEE Trans. Pattern Anal. Mach. Intell. 15 1 1993 37-50
29. Kanatani K. 3-D interpretation of optical flow by renormalization Int. J. Comput. Vision 11 3 1993 267-282
30. Tomasi C. Kanade T. Shape and motion from image streams under orthography Int. J. Comput. Vision 9 2 1992 137-154
31. C. Tomasi, J. Shi, Direction of heading from image deformations, in: Proceedings of Computer Vision and Pattern Recognition, New York City, NY, 1993, pp. 422-427.
32. J. Shi, C. Tomasi, Good features to track, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Seattle, 1994.
33. M.J. Brooks, W. Chojnacki, A. Van Den Hengel, L. Baumela, Robust techniques for the estimation of structure from motion in the uncalibrated case, in: Proceedings of the Fifth European Conference on Computer Vision, Vol. 1, Freiburg, Germany, 1998, pp. 281-295.
34. Y. Ma, J. Košecká, S. Sastry, Motion recovery form images sequences: Discrete viewpoint vs. differential viewpoint, in: Proceedings of the 15th European Conference on Computer Vision, Freiburg, Germany, 1998.
35. L. Baumela, L. Agapito, P. Bustos, I. Reid, Motion estimation using the differential epipolar equation, Proceedings of the Fifteenth International Conference on Pattern Recognition, Barcelona, Spain, Vol. 3, 2000, pp. 848-851.
36. Horn B.K. Relative orientation Int. J. Comput. Vision 4 1990 59-78
37. Prazdny K. Egomotion and relative depth map from optical flow Biol. Cybernet. 36 1980 87-102
38. Prazdny K. Determining the instantaneous direction of motion from optical flow generated by a curvilinearly moving observer Comput. Graphics Image Process. 17 1981 238-248
39. Weng J. Ahuja N. Huang T.S. Matching two prespective views IEEE Trans. Pattern Anal. Mach. Intell. 14 1992 806-825
40. Bruss A.R. Horn B.K. Passive navigation Comput. Vision Graphics Image Process. 21 1983 3-20
41. Taylor C.J. Kriegman D.J. Structure and motion from line segments in multiple images IEEE Trans. Pattern Anal. Mach. Intell. 17 11 1995 1021-1032
42. T. Zhang, C. Tomasi, Fast, robust, and consistent camera motion estimation, in: Proceedings of the IEEE Computer Vision and Pattern Recognition, Ft. Collins, CO, Vol. 1, 1999, pp. 164-170.
43. S. Soatto, R. Brockett, Optimal and suboptimal structure from motion, in: Proceedings of the IEEE International Conference on Computer Vision, Santa Barbara, CA, 1998, pp. 282-288.
44. Y. Ma, J. Košecká, S. Sastry, Optimal motion from image sequences: A riemannian viewpoint, in: Proceedings of the Conference on Mathematical Theory of Networks and Systems, Padova, Italy, 1998.
45. Rousseeuw P.J. Leroy A.M. Robust Regression and Outlier Detection 1987 Wiley New York
46. Ruhe A. Wedin P.A. Algorithms for separable nonlinear least squares problems SIAM Rev. 22 3 1980 318-337
47. Hutchinson S. Hager G.D. Corke P.I. A tutorial on visual servo control IEEE Trans. Robotics Automat. 12 5 1996 651-670
48. T.Y. Tian, C. Tomasi, D.J. Heeger, Comparison of approaches to egomotion computation, in: Proceedings of Computer Vision and Pattern Recognition, San Francisco, CA, 1996, pp. 315-320.