Robust techniques for the estimation of structure from motion in the uncalibrated case

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1406, Issue , 1998, Pages 281-295

  Brooks, Michael J ^a   Chojnacki, Wojciech ^a   van den Hengel, Anton ^a   Baumela, Luis ^b  

^a UNIVERSITY OF ADELAIDE   (Australia)

^b UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE PROCESSING; LEAST SQUARES APPROXIMATIONS; OPTICAL FLOWS;

CLOSED-FORM EXPRESSION; DEPENDENCY CONSTRAINTS; LEAST SQUARES METHODS; REAL IMAGE SEQUENCES; RECOVERY PROCESS; ROBUST TECHNIQUE; STRUCTURE FROM MOTION; STRUCTURE RECOVERY;

COMPUTER VISION;

EID: 84957686816     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/BFb0055673     Document Type: Conference Paper

References (29)

1. M. Armstrong, A. Zisserman, and R. Hartley, Self-calibration from image triplets, In Buxton and Cipolla [8], pp. 3-16.
2. K. Åström and A. Heyden, Continuous time matching constraints for image streams, International Journal of Computer Vision, to appear.
3. K. Åström and A. Heyden, Multilinear forms in the infinitesimal-time case, Proceedings, CVPR '96, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (San Francisco, CA, June 18-20, 1996), IEEE Computer Society Press, Los Alamitos, CA, 1996, pp. 833- 838.
4. J. L. Barron and R. Eagleson, Recursive estimation of time-varying motion and structure parameters, Pattern Recognition 29 (1996), no. 5, 797-818.
5. P. A. Beardsley, A. Zisserman, and D. W. Murray, Sequential updating of projective and affine structure from motion, International Journal of Computer Vision 23 (1997), no. 3, 235-259.
6. F. Bookstein, Fitting conic sections to scattered data, Computer Vision, Graphics, and Image Processing? (1979), no. 1,56-71.
7. M. J. Brooks, W. Chojnacki, and L. Baumela, Determining the egomotion of an uncalibrated camera from instantaneous optical flow, Journal of the Optical Society of America A 14 (1997), no. 10, 2670-2677.
8. B. Buxton and R. Cipolla (eds.), Computer Vision-ECCV '96, Lecture Notes in Computer Science, vol. 1064, Fourth European Conference on Computer Vision, Cambridge, UK, April 14-18,1996, Springer, Berlin, 1996.
9. O. D. Faugeras, Q. T. Luong, and S. J. Maybank, Camera self-calibration: Theory and experiments, Computer Vision-ECCV '92 (Second European Conference on Computer Vision, Santa Margherita Ligure, Italy, May 19-22,1992) (G. Sandini, ed.), Springer, Berlin, 1992, pp. 321-334.
10. N. C. Gupta and L. N. Kanal, 3-D motion estimation from motion field, Artificial Intelligence 78 (1995), no. 1-2,45-86.
11. D. J. Heeger and A. D. Jepson, Subspace methods for recovering rigid motion I: algorithm and implementation, International Journal of Computer Vision 7 (1992), no. 2, 95-117.
12. K. Kanatani, 3-D interpretation of optical flow by renormalization, International Journal of Computer Vision 11 (1993), no. 3, 267-282.
13. K. Kanatani, Statistical Optimization for Geometric Computation: Theory and Practice, Elsevier, Amsterdam, 1996.
14. Q.-T. Luong and O. D. Faugeras, The fundamental matrix: theory, algorithms, and stability analysis, International Journal of Computer Vision 17 (1996), no. 1, 43-75.
15. Q.-T. Luong and O. D. Faugeras, Self-calibration of a moving camera from point correspondences and fundamental matrices, International Journal of Computer Vision 22 (1997), no. 3, 261-289.
16. S. J. Maybank, The angular velocity associated with the optical flowfield arising from motion through a rigid environment, Proceedings of the Royal Society of London Ser. A 401 (1985), 317-326.
17. S. J. Maybank and O. D. Faugeras, A theory of self-calibration of a moving camera, International Journal of Computer Vision 8 (1992), no. 2,123-151.
18. N. Ohta and K. Kanatani, Optimal structure-from-motion algorithm for optical flow, IEICE Transactions on Information and Systems E78-D (1995), no. 12,1559-1566.
19. M. Pollefeys, M. Van Gool, and M. Proesmans, Euclidean 3D reconstruction from image sequences with variable focal length, In Buxton and Cipolla [8], pp. 31-42.
20. W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes in C, Cambridge University Press, Cambridge, 1995.
21. P. J. Rousseeuw and A. M. Leroy, Robust Regression and Outlier Regression, John Wiley & Sons, New York, 1987.
22. P. D. Sampson, Fitting conics sections to 'very scattered' data: An iterative refinement of the Bookstein algorithm, Computer Graphics and Image Processing 18 (1982), no. 1, 97-108.
23. S. Soatto and P. Perona, Recursive 3D visual motion estimation using subspace constraints, International Journal of Computer Vision 22 (1997), no. 3,235-259.
24. P. H. S. Torr and D. W. Murray, The development and comparison of robust methods for estimating the fundamental matrix, International Journal of Computer Vision 24 (1997), no. 3, 271-300.
25. T. Viéville and O. D. Faugeras, Motion analysis with a camera with unknown, and possibly varying intrinsic parameters, Proceedings of the Fifth International Conference on Computer Vision (Cambridge, MA, June 1995), IEEE Computer Society Press, Los Alamitos, CA, 1995, pp. 750-756.
26. T. Viéville, O. D. Faugeras, and Q.-T. Luong, Motion of points and lines in the uncalibrated case, International Journal of Computer Vision 17 (1996), no. 1,7-41.
27. T. Viéville, C. Zeller, and L. Robert, Using collineations to compute motion and structure in an uncalibrated image sequence, International Journal of Computer Vision 20 (1996), no. 3, 213-242.
28. J. Weng, T. S. Huang, and N. Ahuja, Motion and structure from two perspective views: algorithms, error analysis, and error estimation, IEEE Transactions on Pattern Analysis and Machine Intelligence 11 (1989), no. 5,451-476.
29. Z. Zhang, Parameter estimation techniques: a tutorial with application to conic fitting, Image and Vision Computing 15 (1997), no. 1, 57-76.