Christmas, J., Everson, R. M., Bell, James Stephen ![]() |
Official URL: http://dx.doi.org/10.1016/j.patcog.2014.04.022
Abstract
We introduce a novel Bayesian inexact point pattern matching model that assumes that a linear transformation relates the two sets of points. The matching problem is inexact due to the lack of one-to-one correspondence between the point sets and the presence of noise. The algorithm is itself inexact; we use variational Bayesian approximation to estimate the posterior distributions in the face of a problematic evidence term. The method turns out to be similar in structure to the iterative closest point algorithm.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Optometry and Vision Sciences |
Publisher: | Elsevier |
ISSN: | 0031-3203 |
Date of Acceptance: | 26 April 2014 |
Last Modified: | 31 Oct 2022 10:46 |
URI: | https://orca.cardiff.ac.uk/id/eprint/86064 |
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