Structure and Motion from Line Segments in Multiple Images

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 17, Issue 11, 1995, Pages 1021-1032

  Kriegman, David J ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b YALE UNIVERSITY   (United States)

Author keywords

numerical minimization; perspective projection; straight lines; Structure from motion; three dimensional reconstruction

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; IMAGE ANALYSIS;

LINE SEGMENTS; MULTIPLE IMAGES; NUMERICAL MINIMIZATION; PERSPECTIVE PROJECTION; STRUCTURE FROM MOTION (SFM) PROBLEM;

IMAGE RECONSTRUCTION;

EID: 0029406172     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/34.473228     Document Type: Article

References (30)

1. S. Ullman, The Interpretation of Visual Motion. Cambridge, Mass.: MIT Press, 1979.
2. H.C. Longuet-Higgins, “A computer algorithm for reconstructing a scene from two projections,” Nature, vol. 293, pp. 133–135, 1981.
3. J. Weng, T.S. Huang, and N. Ahuja, “Motion and structure from two perspective views: Algorithms, error analysis, and error estimation,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, no. 5, pp. 451–476, May 1989.
4. X. Hu and N. Ahuja, “Motion and structure estimation using long sequence motion models,” Image and Vision Computing, vol. 11, no. 9, pp. 549–570, Nov. 1993.
5. B.K.P. Horn, “Relative orientation,” Int'l J. Computer Vision, vol. 4, pp. 59–78, 1990.
6. J. Weng, T. S. Huang, and N. Ahuja, Motion and Structure from Image Sequences, Springer Series on Information Sciences. Berlin: Springer-Verlag, 1993.
7. J.L. Crowley, P. Stelmaszyk, T. Skordas, and P. Puget, “Measurement and integration of 3D structures by tracking edge lines,” Int'l J. Computer Vision, vol. 8, no. 1, pp. 29–52, July 1992.
8. O.D. Faugeras, F. Lustaman, and G. Toscani, “Motion and structure from point and line matches,” Proc. Int'l Conf. Computer Vision, pp. 25–33, June 1987.
9. J.L. Jezouin and N. Ayache, “3D structure from a monocular sequence of images,” Proc. Int'l Conf. Computer Vision, p. 441, Dec. 1990.
10. T. Vieville and O. Faugeras, “Feed-forward recovery of motion and structure from a sequence of 2D-lines matches,” Proc. Int'l Conf. Computer Vision, p. 517, Dec. 1990.
11. C. Tomasi and T. Kanade, “Shape and motion from image streams under orthography: A factorization method,” Int'l J. Computer Vision, vol. 9, no. 2, pp. 137–154, Nov. 1992.
12. R. Szeliski and S.B. Kang, “Recovering 3D shape and motion from image streams using nonlinear least squares,” J. Visual Communication and Image Representation, vol. 5, no. 1, pp. 10–28, Mar. 1994.
13. T. Vieville, “Estimation of 3D-motion and structure from tracking 2D-lines in a sequence of images,” Proc. European Conf. Computer Vision, p. 281, Apr. 1990.
14. B. Giai-Checa and T. Vieville, “3D-vision for active visual loops using locally rectilinear edges,” Proc. 1992 IEEE Int'l Symp. Intelligent Control, p. 341, Aug. 1992.
15. N. Navab, R. Deriche, and O.D. Faugeras, “Recovering 3D motion and structure from stereo and 2D token tracking,” Proc. Int'l Conf. Computer Vision, p. 513, Dec. 1990.
16. J. Weng, Y. Liu, T.S. Huang, and N. Ahuja, “Estimating motion/structure from line correspondences: A robust linear algorithm and uniqueness theorems,” Proc. IEEE Conf. Comp. Vision and Pattern Recognition, pp. 387–392, 1988.
17. M.E. Spetsakis and J. Aloimonos, “Structure from motion using line correspondences,” Int'l J. Computer Vision, vol. 4, no. 3, pp. 171–184, June 1990.
18. M. Spetsakis, “A linear algorithm for point and line based structure from motion,” CVGIP:Image Understanding, vol. 56, no. 2, Sept. 1992.
19. O. Faugeras, Three-Dimensional Computer Vision. Cambridge, Mass.: MIT Press, 1993.
20. C.J. Taylor, D.J. Kriegman, and P. Anandan, “Structure and motion in two dimensions from multiple images: A least squares approach,” IEEE Workshop Visual Motion, pp. 242–248, Oct. 1991.
21. J. Canny, “A computational approach to edge detection,” IEEE Trans. Pattern Analysis and Machine Intelligence, pp. 679–98, Nov. 1986.
22. J. Craig, Introduction to Robotics: Mechanics and Control. New York: Addison-Wesley, 1989.
23. G.H. Golub and C.F. Van Loan, Matrix Computations. Baltimore, Md.: Johns Hopkins Univ. Press, 1983.
24. Y. Liu, T.S. Huang, and O.D. Faugeras, “Determination of camera location from 2D to 3D line and point correspondences,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 82–88, 1988.
25. R. Kumar and A.R. Hanson, “Robust estimation of camera location and orientation from noisy data having outliers,” Proc. Workshop on the Interpretation of 3D Scenes, pp. 52–60, Nov. 1989.
26. C.J. Taylor and D.J. Kriegman, “Minimization on the lie group SO(3) and related manifolds,” Technical Report 9405, Center for Systems Science, Dept. of Electrical Engineering, Yale Univ., New Haven, Conn., Apr. 1994.
27. S Smith, “Geometric Optimization Methods for Adaptive Filtering,” PhD thesis, Harvard Univ., Division of Applied Sciences, Cambridge Mass., Sept. 1993.
28. M.M. Thompson, Manual of Photogrammetry. American Society of Photogrammetry, 1966.
29. Y. Liu and T.S. Huang, “A linear algorithm for motion estimation using straight line correspondences,” Computer Vision, Graphics, and Image Processing, vol. 44, no. 1, pp. 35–57, Oct. 1988.
30. K. Sugihara, “An algebraic approach to the shape-from-image problem,” Artificial Intelligence, vol. 23, pp. 59–95, 1984.