Recovering Perspective Pose with a Dual Step EM Algorithm

Part of Advances in Neural Information Processing Systems 10 (NIPS 1997)

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Andrew Cross, Edwin Hancock


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 point(cid:173) correspondence matches. Unification is realised by constructing a mixture model over the bi-partite graph representing the correspon(cid:173) dence match and by effecting optimisation using the EM algorithm. According to our EM framework the probabilities of structural cor(cid:173) respondence gate contributions to the expected likelihood function used to estimate maximum likelihood perspective pose parameters. This provides a means of rejecting structural outliers.