Four points in two or three calibrated views: Theory and practice

International Journal of Computer Vision

Volumn 67, Issue 2, 2006, Pages 211-231

  Nistér, David ^a   Schaffalitzky, Frederik ^b  

^a SARNOFF CORPORATION   (United States)

^b UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

Algebraic curves; Kruppa constraint; Minimal methods; Multi view geometry; RANSAC; Structure from motion

Indexed keywords

CAMERAS; COMPUTER ARCHITECTURE; CONSTRAINT THEORY; MATRIX ALGEBRA; PROBLEM SOLVING;

KRUPPA CONSTRAINT; MULTI-VIEW GEOMETRY; RANSAC; STRUCTURE-FROM-MOTION;

IMAGE ANALYSIS;

EID: 33646507079     PISSN: 09205691     EISSN: 15731405     Source Type: Journal    
DOI: 10.1007/s11263-005-4265-x     Document Type: Conference Paper

References (15)

1. Faugeras, O. D. 1993. Three-Dimensional Computer Vision: A Geometric Viewpoint. MIT Press.
2. Fischler, M.A. and Bolles, R.C. 1981. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Comm. Assoc. Comp. Mach. 24(6), 381-395.
3. Haralick, R.M., Lee, C., Ottenberg, K., and Nölle, M. 1994. Review and analysis of solutions of the three point perspective pose estimation problem. Int. J. of Computer Vision. 13(3), 331-356.
4. Hartley, R.I. and Zisserman, A. 2000. Multiple View Geometry in Computer Vision, Cambridge University Press.
5. Holt, R. and Netravali, A. 1995. Uniqueness of solutions to three perspective views of four points. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(3).
6. Kirwan, F. 1995. Complex Algebraic Curves, Cambridge University Press.
7. Maybank, S.J. 1993. Theory of Reconstruction from Image Motion. Berlin: Springer-Verlag.
8. Nistér, D. 2003a. An efficient solution to the five-point relative pose problem. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Madison, Wisconsin, Vol. 2. pp. 195-202.
9. Nistér D. 2003b. Preemptive RANSAC for live structure and motion estimation. In Proceedings of the International Conference on Computer Vision, pp. 199-206.
10. Nistér, D. 2004. An Efficient solution to the five-point relative pose problem. IEEE Transactions on Pattern Analysis and Machine Intelligence 26(6), 756-770. To appear.
11. Quan, L., Triggs, B., and Mourrain, B. 2003a. Some results on minimal euclidean reconstruction from four points. J. of Math. Imag. and Vision. To appear.
12. Quan, L., Triggs, B., Mourrain, B. and Ameller, A. 2003b. Uniqueness of minimal euclidean reconstruction from 4 points. Unpublished article.
13. Schaffalitzky, F., Zisserman, A., Hartley, R.I., and Torr, P.H.S. 2000. A six point solution for structure and motion. In Proceedings of the European Conference on Computer Vision, pp. 632-648, Springer-Verlag.
14. Semple, J.G. and Kneebone, G.T. 1952. Algebraic Projective Geometry. Oxford University Press.
15. Werner, T. 2003. Constraints on five points in two images. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Madison, Wisconsin, vol. 2. pp. 203-208.