An algorithm for centroid-based tracking of moving objects

Author

Nascimento, Jacinto C. ; Abrantes, Arnaldo J. ; Marques, Jorge S.

Author_Institution

Inst. Superior Tecnico, Lisbon, Portugal

Volume

6

fYear

1999

fDate

15-19 Mar 1999

Firstpage

3305

Abstract

This article addresses the problem of tracking moving objects using deformable models. A Kalman-based algorithm is presented, inspired by a new class of constrained clustering methods, proposed by Abrantes and Marques (1996) in the context of static shape estimation. A set of data centroids is tracked using intra-frame and inter-frame recursions. Centroids are computed as weighted sums of the edge points belonging to the object boundary. The use of centroids introduces competitive learning mechanisms in the tracking algorithm leading to improved robustness with respect to occlusion and contour sliding. Experimental results with traffic sequences are provided

Keywords

Kalman filters; edge detection; image motion analysis; image sequences; object detection; optical tracking; tracking; unsupervised learning; video signal processing; Kalman-based algorithm; centroid-based tracking; competitive learning mechanisms; constrained clustering methods; contour sliding; data centroids; deformable models; edge points; inter-frame recursions; intra-frame recursions; moving objects; object boundary; occlusion; robustness; static shape estimation; traffic sequence; Deformable models; Image analysis; Kalman filters; Layout; Motion estimation; Robustness; Shape; State estimation; Tracking; Trajectory;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on

Conference_Location

Phoenix, AZ

ISSN

1520-6149

Print_ISBN

0-7803-5041-3

Type

conf

DOI

10.1109/ICASSP.1999.757548

Filename

757548