Abstract
An approach to normalization is presented for both the affine and the projective case. The approach is based on group factorization as well as on optimizing parameter invariant integrals, in order to overcome the difficult problem of parameterization. Related work has been carried out by [6] and by [4] for affine transformations and by [5] for projective transformations. To avoid some drawbacks inherent to projective transformations it is suitable to integrate point information or explore ’thick’ curves.
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© 1996 Springer-Verlag Berlin Heidelberg
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Schiller, R. (1996). Normalization by optimization. In: Buxton, B., Cipolla, R. (eds) Computer Vision — ECCV '96. ECCV 1996. Lecture Notes in Computer Science, vol 1064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0015572
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DOI: https://doi.org/10.1007/BFb0015572
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