Abstract

In this study, the problem of fitting shape primitives to point cloud scenes was tackled 2 as a parameter optimisation procedure and solved using the popular Bees Algorithm. Tested on three sets of clean and differently blurred point cloud models, the Bees Algorithm obtained performances comparable to those obtained using the state-of-the-art RANSAC method, and superior to those obtained by an evolutionary algorithm. Shape fitting times were compatible with the real-time application. The main advantage of the Bees Algorithm over standard methods is that it doesn’t rely on ad hoc assumptions about the nature of the point cloud model like RANSAC approximation tolerance.