Registration Framework using Mixture Models

  title={Registration Framework using Mixture Models},
  author={Haili Chui and Anand Rangarajan},
We formulate feature registration problems as maximum likelihood or Bayesian maximum a posteriori estimation problems using mixture models. An EM-like algorithm is proposed to jointly solve for the feature correspondences as well as the geometric transformations. A novel aspect of our approach is the embedding of the EM algorithm within a deterministic annealing scheme in order to directly control the fuzziness of the correspondences. The resulting algorithm— termed mixture point matching (MPM… CONTINUE READING


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