Abstract
In this paper we present a novel representation for arbitrary surfaces that enables local correspondences to be determined. We then describe how these local correspondences can be used to search for the transformation that best aligns all of surface data. If this transformation is found to align a significant proportion of the surface data then the surfaces are said to have a correspondence.
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References
Evans, A. C., “Geometric Feature Distributions for Shape Representation and Recognition”, Submitted for Ph.D. at the University of Sheffield, 1994.
Ashbrook, A. P., Fisher, R. B., Robertson, C. and Werghi, N., “Finding Surface Correspondence for Object Recognition and Registration using Pairwise Geometric Histograms”, To appear at ECCV98, Freiburg, Germany.
Fischler, M. A. and Bolles, R. C., “Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography”, Communications of the ACM, Vol. 24, pp381, 1981.
Hoppe, H., DeRose, T., Duchamp, T., McDonald, J. and Stuetzle, W., “Surface Reconstruction from Unorganised Points”, Computer Graphics, 26(2), pp71–78, 1992.
Garland, M. and Heckbert, P. S., “Surface Simplification using Quadric Error Metrics”, SIGGRAPH97, pp209–216, 1997.
Besl, P. J. and McKay, N. D., “A method for registration of 3-D shapes”, IEEE PAMI, 14(2), pp 239–256, 1992.
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© 1998 Springer-Verlag London Limited
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Ashbrook, A.P., Fisher, R.B., Werghi, N., Robertson, C. (1998). Aligning Arbitrary Surfaces using Pairwise Geometric Histograms. In: Marshall, S., Harvey, N.R., Shah, D. (eds) Noblesse Workshop on Non-Linear Model Based Image Analysis. Springer, London. https://doi.org/10.1007/978-1-4471-1597-7_16
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DOI: https://doi.org/10.1007/978-1-4471-1597-7_16
Publisher Name: Springer, London
Print ISBN: 978-3-540-76258-4
Online ISBN: 978-1-4471-1597-7
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