Bayesian Approach for fitting Geometric Models in 3D Point Clouds

by William Nguatem for Point Cloud Library (PCL)

A proposal for a Bayesian approach to localize and fit geometric models of objects in 3D point clouds is made. The algorithm would allow the modelling of abitrary shaped objects through the usage of a B-Spline representation. We propose the usage of a likelihood function similar to MSAC to score individual models. Being fully Bayesian, object searching and fitting would provide a complete statistics. This renders inference making easy.