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Inexact Bayesian point pattern matching for linear transformations

Christmas, J., Everson, R. M., Bell, James Stephen ORCID: and Winlove, C. P. 2014. Inexact Bayesian point pattern matching for linear transformations. Pattern Recognition 47 (10) , pp. 3265-3275. 10.1016/j.patcog.2014.04.022

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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
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

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