Primitive Shape Fitting in Point Clouds Using the Bees Algorithm

Baronti, Luca and Alston, Mark and Mavrakis, Nikos and Ghalamzan Esfahani, Amir Masoud and Castellani, Marco (2019) Primitive Shape Fitting in Point Clouds Using the Bees Algorithm. Advances in Automation and Robotics, 9 (23). ISSN 2076-3417

Full content URL: https://doi.org/10.3390/app9235198

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Primitive Shape Fitting in Point Clouds Using the Bees Algorithm
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Item Type:Article
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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.

Keywords:Machine vision, Primitive shape fitting, Genetic algorithms
Subjects:G Mathematical and Computer Sciences > G740 Computer Vision
H Engineering > H671 Robotics
Divisions:College of Science > School of Computer Science
ID Code:39027
Deposited On:02 Dec 2019 09:43

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