Two view NURBS reconstruction based on GACO model

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