Title :
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
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;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on
Conference_Location :
Phoenix, AZ
Print_ISBN :
0-7803-5041-3
DOI :
10.1109/ICASSP.1999.757548
