Image data simplification using spherical and ellipsoidal primitives

Author

Calafiore, Giuseppe

Author_Institution

Dipt. di Automatica e Informatica, Politecnico di Torino, Italy

Volume

2

fYear

2001

fDate

2001

Firstpage

771

Abstract

This paper discusses the problem of approximating data points in n-dimensional Euclidean space, using spherical and ellipsoidal surfaces. For the specific cases of n = 2 and n = 3, the problem is of fundamental importance id computer vision and robotics. A closed form solution is provided for spherical approximation, while an efficient, globally optimal solution for the ellipsoidal problem is proposed in terms of semidefinite programming (SDP). The paper also presents a result for robust fitting in the presence of outliers, and illustrates the theory with several numerical examples

Keywords

computer vision; robot vision; closed form solution; computer vision; data point approximation; ellipsoidal primitives; ellipsoidal surfaces; globally optimal solution; image data simplification; n-dimensional Euclidean space; outliers; robotics; robust fitting; semidefinite programming; spherical approximation; spherical primitives; spherical surfaces; Application software; Closed-form solution; Computer vision; Equations; Least squares approximation; Orbital robotics; Robot programming; Robot vision systems; Robustness; Surface fitting;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 2001 IEEE International Conference on

Conference_Location

Tucson, AZ

ISSN

1062-922X

Print_ISBN

0-7803-7087-2

Type

conf

DOI

10.1109/ICSMC.2001.973008

Filename

973008