Curve and surface reconstruction from points: an approach based on self-organizing maps

Abstract

Abstract Modeling of shapes for free form objects from point cloud is an emerging trend. Recognition of shape from the measured point data is a key step in the process of converting discrete data set into a piecewise smooth, continuous model. Shape recognition is to find the topological relation among the points, and in case of thick unorganized point cloud, the step requires both thinning and ordering. The present paper outlines a new approach based on growing self-organizing maps (GSOM) for piecewise linear reconstruction of curves and surfaces from unorganized thick point data. Inferences on selection of self-organizing map (SOM) algorithm parameters for this problem domain have been derived after extensive experimentation. A better quality measure to evaluate and compare various runs of SOM for the domain of curve and surface reconstruction has also been presented.