Abstract
A new method for solving the stereo matching problem in the presence of large occlusion is presented. A data structure — the disparity space image — is defined in which we explicitly model the effects of occlusion regions on the stereo solution. We develop a dynamic programming algorithm that finds matches and occlusions simultaneously. We show that while some cost must be assigned to unmatched pixels, our algorithm's occlusion-cost sensitivity and algorithmic complexity can be significantly reduced when highly-reliable matches, or ground control points, are incorporated into the matching process. The use of ground control points eliminates both the need for biasing the process towards a smooth solution and the task of selecting critical prior probabilities describing image formation.
Chapter PDF
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
P. Belhumeur. Bayesian models for reconstructing the scene geometry in a pair of stereo images. In Proc. Info. Sciences Conf., Johns Hopkins University, 1993.
R. Bolles, H. Baker, and M. Hannah. The JISCT stereo evaluation. In Proc. Image Understanding Workshop, pages 263–274, 1993.
R.C. Bolles and J. Woodfill. Spatiotemporal consistency checking of passive range data. SRI Technical Report — to be published, SRI International, September 1993.
S.D. Cochran and G. Medioni. 3-d surface description from binocular stereo. IEEE Trans. Patt. Analy. and Mach. Intell., 14(10):981–994, 1992.
I.J. Cox, S. Hingorani, B. Maggs, and S. Rao. Stereo without regularization. NEC Research Institute Report, NEC Research Institute, October 1992.
U.R. Dhond and J.K. Aggarwal. Structure from stereo — a review. IEEE Trans. Sys., Man and Cyber., 19(6):1489–1510, 1989.
D. Geiger, B. Ladendorf, and A. Yuille. Occlusions and binocular stereo. In Proc. European Conf. Comp. Vis., pages 425–433, 1992.
M.J. Hannah. A system for digital stereo image matching. Photogrammetric Eng. and Remote Sensing, 55(12):1765–1770, 1989.
S.S. Intille and A.F. Bobick. Disparity-space images and large occlusion stereo. MIT Media Lab Perceptual Computing Group Technical Report No. 220, Massachusetts Institute of Technology, October 1993.
T. Kanade and M. Okutomi. A stereo matching algorithm with an adaptive window: theory and experiment. In Proc. Image Understanding Workshop, pages 383–389, 1990.
K. Nakayama and S. Shimojo. Da Vinci stereopsis: depth and subjective occluding contours from unpaired image points. Vision Research, 30(11):1811–1825, 1990.
Y. Ohta and T. Kanade. Stereo by intra-and inter-scanline search using dynamic programming. IEEE Trans. Patt. Analy. and Mach. Intell, 7:139–154, 1985.
Y. Yang, A. Yuille, and J. Lu. Local, global, and multilevel stereo matching. In Proc. Comp. Vis. and Pattern Rec., 1993.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1994 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Intille, S.S., Bobick, A.F. (1994). Disparity-space images and large occlusion stereo. In: Eklundh, JO. (eds) Computer Vision — ECCV '94. ECCV 1994. Lecture Notes in Computer Science, vol 801. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0028349
Download citation
DOI: https://doi.org/10.1007/BFb0028349
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-57957-1
Online ISBN: 978-3-540-48400-4
eBook Packages: Springer Book Archive