Two view NURBS reconstruction based on GACO model release_hj2aws4xkrhxtmpeb4upppucwq

by Deepika Saini, SANOJ KUMAR, Manoj K. Singh, Musrrat Ali

Published in Complex & Intelligent Systems by Springer Science and Business Media LLC.

2021  

Abstract

<jats:title>Abstract</jats:title>The key job here in the presented work is to investigate the performance of Generalized Ant Colony Optimizer (GACO) model in order to evolve the shape of three dimensional free-form Non Uniform Rational B-Spline (NURBS) curve using stereo (two) views. GACO model is a blend of two well known meta-heuristic optimization algorithms known as Simple Ant Colony and Global Ant Colony Optimization algorithms. Basically, the work talks about the solution of NURBS-fitting based reconstruction process. Therefore, GACO model is used to optimize the NURBS parameters (control points and weights) by minimizing the weighted least-square errors between the data points and the fitted NURBS curve. The algorithm is applied by first assuming some pre-fixed values of NURBS parameters. The experiments clearly show that the optimization procedure is a better option in a case where good initial locations of parameters are selected. A detailed experimental analysis is given in support of our algorithm. The implemented error analysis shows that the proposed methodology perform better as compared to the conventional methods.
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Date   2021-06-05
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