Information technology for digital terrain model reconstruction from stereo images
V.A. Fursov, Ye.V. Goshin

PDF, 938 kB

Full text of article: Russian language.

DOI: 10.18287/0134-2452-2014-38-2-335-342

Pages: 335-342.

Abstract:
This paper considers an information technology of digital terrain model (DTM) reconstruction from the pair of stereo images. For the case when the camera parameters are known, image matching algorithms based on epipolar constraints are thoroughly considered. In the matching we use weight coefficients as a penalty function for distance from the matching point to the epipolar line. Implementation of the technology when cameras’ parameters are not known is also considered. At the initial stage the problem of identification of the fundamental matrix from the corresponding points is solved. The major advantage of the proposed technology is the lack of the image rectification stage. This improves the reliability of the matching. The results of the proposed technology application for the DTM reconstruction from remote sensing stereo images are given.

Key words:
stereoimages, image matching, digital terrain model, disparity map, conformed identification, fundamental matrix, epipolar geometry.

References:

  1. Hartley, R.I. Theory and Practice of Projective Rectification // International Journal of Computer Vision. – 1999. – V. 35. – P. 115-127.
  2. Monasse, P. Three-step image rectification / P. Monasse,
  3. J.-M. Morel, Z. Tang // Proceedings of the British Machine Vision Conference. – 2010. – V. 19. – P. 89.1-89.10.
  4. Pollefeys, M. A simple and ef?cient recti?cation method for general motion // The Proceedings of the 7th IEEE International Conference on Computer Vision. – 1999. – V. 1. – P. 496-501.
  5. Fursov, V. Conformed Identification of the Fundamental Matrix in the Problem of a Scene Reconstruction, using Stereo Images / V. Fursov, Ye. Goshin // Image Mining. Theory and Applications. Proceedings of IMTA-4 2013. – 2013. – P. 29-37.
  6. Luong, Q.T. The fundamental matrix: Theory, algorithms, and stability analysis / Q.T. Luong, O.D. Faugeras // International Journal of Computer Vision. – 1996 – V. 17(1). – P. 43-75.
  7. Häming, K. Extension of the generalized image rectification – Catching the infinity cases / K. Häming, G. Peters // Proc. 4th International Conference on Informatics in Control, Automation, and Robotics (ICINCO 2007). – 2007 – V. 2. – P. 275-279.
  8. Oram, D. Rectification for any epipolar geometry //British Machine Vision Conference. – 2001. – P. 653-662.
  9. Pollefeys, M. Detailed real-time urban 3d reconstruction from video / M. Pollefeys, D. Nistr, J.M. Frahm [et al.] // International Journal of Computer Vision. – 2008. – V. 78(2-3). – P. 143-167.
  10. Molton, N. Practical structure and motion from stereo when motion is unconstrained / N. Molton, M. Brady // International Journal of Computer Vision. – 2000. – V. 39(1). – P. 5-23.
  11. Vieville, T. Motion of points and lines in the uncalibrated case / T. Vieville, O. Faugeras, Q.T. Luong // International Journal of Computer Vision. – 1996. – V. 17(1). – P. 7-41.
  12. Baha, N. Accurate real-time disparity map computation based on variable support window / N. Baha, S. Larabi // International Journal of Artificial Intelligence & Applications (IJAIA). – 2011. – V. 2. – P. 22-34.
  13. Hartley, R.I. Triangulation / R.I. Hartley, P. Sturm // Computer Vision and Image Understanding. – 1997. – V. 68. – P. 146-157.
  14. Stewart, C.V. Geometric constraints and stereo disparity computation / C.V. Stewart, R.Y. Flatland, K. Bubna // International Journal of Computer Vision. – 1996. – V. 20, Issue 3. – P. 143-168.
  15. Gruzman, I.S. Digital Image Processing in Information systems / I.S. Gruzman, V.S. Kirichuk, V.P. Kosykch [et al.] – Novosibirsk: “NSTU” Publisher, 2002. – 352 p. – (In Russian).
  16. Forsyth, D. Computer Vision: A Modern Approach / David Forsyth, Jean Ponce. – Moscow: “Williams” Publisher, 2004. – 928 p. – (In Russian).
  17. Fursov, V.A. 3D-scene stereo reconstruction on sheaves of epipolar planes / V.A. Fursov, Ye.V. Goshin, S.A. Bibikov // Mechatronics Automation Control. – 2013. – V. 9(150). – P. 19-24. – (In Russian).
  18. Tao, M. SimpleFlow: A Non-iterative, Sublinear Optical Flow Algorithm / M. Tao, J. Bai, P. Kohli, S. Paris// Computer Graphics Forum. – 2012. – V. 31, Issue 2. – P. 345-353.
  19. Kuznesov, P.K. Method for computing velocity of moving objects by image analysis / P.K. Kuznesov, B.V. Martemyanov, V.I. Semavin, E.Yu. Chekotilo // Vestnik of Samara State Technical University (Technical Sciences Series). – 2008. – V. 2(22). – P. 96-110. – (In Russian).
  20. Fursov, V.A. Conformed identification in corresponding points detection problem / V.A. Fursov, Ye.V. Goshin // Computer Optics. – 2012. – V. 36(1). – P. 131-135.
© 2009, IPSI RAS
151, Molodogvardeiskaya str., Samara, 443001, Russia; E-mail: journal@computeroptics.ru ; Tel: +7 (846) 242-41-24 (Executive secretary), +7 (846) 332-56-22 (Issuing editor), Fax: +7 (846) 332-56-20