Approximate Bayesian estimation of a 3D point pattern from multiple views
A Bayesian method is suggested for combining multiple views of different observation accuracies to reconstruct a 3D point pattern, using a Wishart distribution as prior distribution to model varying measurement error variances and covariances. Experiments are performed on synthetic data simulating reconstruction of tree positions from aerial photography and on real data of this type.
wishart distribution heteroscedastic displacement errors bayes estimation conjugate prior distributions posterior mode individual tree positions