Abstract
We are interested in matching stereoscopic images involving both natural objects (vegetation, sky, reliefs,...) and man made objects (buildings, roads, vehicles,...). In this context we have developed a pyramidal stereovision algorithm based on ”contour chain points.” The matching process is performed at different steps corresponding to the different resolutions. The nature of the primitives allows the algorithm to deal with rich and complex scenes. Goods results are obtained for extremely fast computing time.
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N. Ayache and B. Faverjon, ”Fast Stereo Matching of Edges Segments Using Prediction and Verification of Hypotheses”, CVPR, 1985.
R. Deriche, Optimal Edge Detection Using Recursive Filtering, Proceedings of of the first International Conference on Computer Vision (ICCV), pp. 501–505, Londres, 1987.
G. Giraudon, ”Chainage rapide sur des images de contour,” Rapport de recherche INRIA, 1987.
W. E. L. Grimson, ”From Images to surfaces,” MIT Press, Cambridge, 1981.
W. E. L. Grimson, ”Computational Experiments with a Feature Based Stereo Algorithm,” IEEE Trans. PAMI, vol. PAMI-7, pp. 17–34, January 1985.
M. J. Hannah, ”Decription of SRI's Baseline Stereo System,” Technical Note No.342, Artificial Intelligence Center, SRI International, Oct 1984.
N. H. Kim and A. C. Bovik, ”A solution to the Stereo Correspondence Problem Using Disparity Smoothness Constraint,” Proc. of IEEE Conf. Systems, Man, and Cybernetics, Atlanta, October 1986.
P.Limozin-Long, ”Stereo Matching Using Contextual Line Region Primitives,” ICPR Paris, Oct 1986.
D. Marr and T. Poggio, ”A theory of Human Stereo Vision”, Proc. R. Soc. Lond.’ vol. B 204, pp. 301–328, 1979.
J.E.W. Mayhew and J.P. Frisby, ”Psychophysical and computational studies towards a theory of human stereopsis,” Artif.Intell., 17, pp. 349–385, 1981.
G. Medioni and R. Nevatia, ”Segment-Based Stereo Matching”, Computer Vision, Graphics, ang Image Processing, vol. 31, pp. 2–18, July 1985.
B. Wrobel-Dautcourt, ”Coopération entre l'extraction et la mise en correspondance symbolique de régions,” MARI Paris, pp 181–188, 1987
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© 1990 Springer-Verlag Berlin Heidelberg
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Meygret, A., Thonnat, M., Berthod, M. (1990). A pyramidal stereovision algorithm based on contour chain points. In: Faugeras, O. (eds) Computer Vision — ECCV 90. ECCV 1990. Lecture Notes in Computer Science, vol 427. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0014853
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DOI: https://doi.org/10.1007/BFb0014853
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