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Advisor(s)
Abstract(s)
This paper addresses the estimation of object boundaries from a set of 3D points. An
extension of the constrained clustering algorithm developed by Abrantes and Marques in the
context of edge linking is presented. The object surface is approximated using rectangular
meshes and simplex nets. Centroid-based forces are used for attracting the model nodes
towards the data, using competitive learning methods. It is shown that competitive learning
improves the model performance in the presence of concavities and allows to discriminate
close surfaces. The proposed model is evaluated using synthetic data and medical images
(MRI and ultrasound images).
Description
Keywords
3D surfaces Algoritmh Competitive learning
Citation
NASCIMENTO, José M. P. ; MARQUES, Jorge Salvador - An algoritmh for the estimation of 3D surfaces using competitive learning. Proceedings of the V Ibero-American Symposium on Pattern Recognition - SIARP. Vol. I. pp. 139-146, 2000