Abstract
We consider the potentialities of matching multiple views of a 3D scene by the least square correlation provided that relative projective geometric distortions of the images are affinely approximated. The affine transformation yielding the (sub)optimal match is obtained by combining an exhaustive and directed search in the parameter space. The directed search is performed by a proposed modification of the Hooke-Jeeves unconstrained optimization. Experiments with the RADIUS multipleview images of a model board show a feasibility of this approach.
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© 2001 Springer-Verlag Berlin Heidelberg
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Gimel’farb, G., Zhong, J. (2001). Matching Multiple Views by the Least Square Correlation. In: Klette, R., Gimel’farb, G., Huang, T. (eds) Multi-Image Analysis. Lecture Notes in Computer Science, vol 2032. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45134-X_8
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DOI: https://doi.org/10.1007/3-540-45134-X_8
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