Hybrid particle filtering for real time object tracking

Author

Lanvin, P. ; Noyer, J.C. ; Benjelloun, M. ; Yeary, M. ; Zhai, Y.

Author_Institution

Lab. d´´Analyse des Syst. du Littoral, Universite du Littoral Cote d´´Opale

fYear

2005

fDate

Oct. 28 2005-Nov. 1 2005

Firstpage

761

Lastpage

764

Abstract

This paper presents a method for real time object tracking. The method tracks 3D objects in image sequences and jointly estimates their 3D pose and motion parameters. The solution relies on a state modeling of this estimation problem. We develop a resolution method based on a sequential Monte Carlo method and more particularly on a hybrid particle filter. This approach combines the benefits of the linear filtering with those of the nonlinear filtering by using the linear part of state equations. The proposed method allows a significant reduction in running time and preserves the optimality of the processing. As a consequence, the proposed method allows a real time object tracking

Keywords

Monte Carlo methods; image sequences; nonlinear filters; particle filtering (numerical methods); sequential estimation; hybrid particle filtering; image sequences; nonlinear filtering; real time object tracking; sequential Monte Carlo method; Application software; Computer vision; Filtering; Image sequences; Motion estimation; Nonlinear equations; Nonlinear filters; Particle filters; Particle tracking; Target tracking;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 2005. Conference Record of the Thirty-Ninth Asilomar Conference on

Conference_Location

Pacific Grove, CA

ISSN

1058-6393

Print_ISBN

1-4244-0131-3

Type

conf

DOI

10.1109/ACSSC.2005.1599855

Filename

1599855