Recovering Perspective Pose with a Dual Step EM Algorithm

Cross, Andrew D. J., Hancock, Edwin R.

Neural Information Processing Systems 

This paper describes a new approach to extracting 3D perspective structure from 2D point-sets. The novel feature is to unify the tasks of estimating transformation geometry and identifying pointcorrespondence matches.Unification is realised by constructing a mixture model over the bipartite graph representing the correspondence matchand by effecting optimisation using the EM algorithm. According to our EM framework the probabilities of structural correspondence gatecontributions to the expected likelihood function used to estimate maximum likelihood perspective pose parameters. This provides a means of rejecting structural outliers.

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