Deformable shapes detection by stochastic optimization

Author

González-Linares, J.M. ; Guil, N. ; Zapata, E.L. ; Ortigosa, P.M. ; García, I.

Author_Institution

Dept. of Comput. Archit., Malaga Univ., Spain

Volume

1

fYear

2000

fDate

2000

Firstpage

780

Abstract

A new approach to the detection of shapes under global deformations is presented. The algorithm is based in the combination of a generalized Hough transform (GHT) and an universal evolutionary global optimizer (UEGO). This method exploits the invariant characteristics to rotation, scale and displacement of the GHT to detect shapes deformed by a global deformation model, and without an initial positioning of the template. The GHT is used as an objective function for the UEGO, an optimizer that is able to find multiple optima with a low computational cost

Keywords

Hough transforms; computational complexity; object detection; optimisation; stochastic processes; computational complexity reduction; deformable shapes detection; displacement variation; generalized Hough transform; global deformation model; global deformations; invariant characteristics; low computational cost; object detection; objective function; rotation variation; scale variation; stochastic optimization; universal evolutionary global optimizer; Active shape model; Clustering algorithms; Computational complexity; Computational efficiency; Computer architecture; Deformable models; Finite element methods; Robustness; Sampling methods; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2000. Proceedings. 2000 International Conference on

Conference_Location

Vancouver, BC

ISSN

1522-4880

Print_ISBN

0-7803-6297-7

Type

conf

DOI

10.1109/ICIP.2000.901075

Filename

901075