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Abstract: In this paper we investigate extending the gradient-based inverse compositional image alignment method described by Baker and Matthews [1] by formulating the alignment process probabilistically using Bayes rule to obtain a posterior estimate of the alignment. The probabilistic formulation makes use of prior statistical information on the aligning function parameters, and we investigate the use of arbitrary parameterisation of this function to match the physical system generating the warp. (Update)
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BibTeX entry: (Update)
N. D. Molton, A. Davison, and I. Reid, "Parameterisation and probability in image alignment," Report OUEL 2266/03, Department of Engineering Science, University of Oxford (Available from http:/www.robots.ox.ac.uk/ndm/), Aug. 2003. http://citeseer.ist.psu.edu/article/molton04parameterisation.html More
@misc{ molton03parameterisation,
author = "N. Molton and A. Davison and I. Reid",
title = "Parameterisation and probability in image alignment",
text = "N. D. Molton, A. Davison, and I. Reid, Parameterisation and probability
in image alignment, Report OUEL 2266/03, Department of Engineering Science,
University of Oxford (Available from http:/www.robots.ox.ac.uk/ndm/), Aug.
2003.",
year = "2003",
url = "citeseer.ist.psu.edu/article/molton04parameterisation.html" }
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