A hybrid approach to the recovery of deformable superquadric models from 3D data

Author

Sinnott, James ; Howard, Toby

Author_Institution

Dept. of Comput. Sci., Manchester Univ., UK

fYear

2001

fDate

2001

Firstpage

131

Lastpage

138

Abstract

The problem of recovering the shape of objects from three-dimensional data is important to many areas of computer graphics and vision. We present here a method for the recovery of single-part objects from unstructured 3D points sets, based on the fitting of deformable superquadric models. The limitations of least-squares minimisation as a technique for fitting superquadric models are discussed. After investigating the possibility of using a genetic algorithm as an alternative, we propose a hybrid approach to the recovery of deformable superquadrics based on a two-stage fitting process that combines a genetic algorithm and nonlinear least-squares minimization

Keywords

computer graphics; least squares approximations; minimisation; 3D data; computer graphics; deformable superquadric models; genetic algorithm; hybrid approach; least-squares minimisation; nonlinear least-squares minimization; single-part objects; two-stage fitting process; Computer graphics; Computer science; Computer vision; Deformable models; Genetic algorithms; Medical robotics; Minimization methods; Parametric statistics; Shape control; Solids;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Graphics International 2001. Proceedings

Conference_Location

Hong Kong

ISSN

1530-1052

Print_ISBN

0-7695-1007-8

Type

conf

DOI

10.1109/CGI.2001.934667

Filename

934667