Abstract
This paper describes how mixtures of Gussins be used for multiple shape template registration . The EM algorithm is applied to the shape mixture model to compute both maximum likelihood registration parameters together with set of a posteriori matching probabilities. This architecture can be viewed as providing simultaneous registration and hypothesis verification. The different templates compete to account for data through the imposed probability normalisation. Based on a sensitivity study, our main conclusions are the method is both robust to added noise and poor initialisation.
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© 1997 Springer-Verlag Berlin Heidelberg
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Moss, S., Hancock, E.R. (1997). Image registration with shape mixtures. In: Del Bimbo, A. (eds) Image Analysis and Processing. ICIAP 1997. Lecture Notes in Computer Science, vol 1311. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63508-4_120
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DOI: https://doi.org/10.1007/3-540-63508-4_120
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