Share Email Print
cover

Proceedings Paper

Linear stereo vision based objects detection and tracking using spectral clustering
Author(s): Safaa Moqqaddem; Y. Ruichek; R. Touahni; A. Sbihi
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Objects detection and tracking is a key function for many applications like video surveillance, robotic, intelligent transportation systems,...etc. This problem is widely treated in the literature in terms of sensors (video cameras, laser range finder, Radar) and methodologies. This paper proposes a new approach for detecting and tracking objects using stereo vision with linear cameras. After the matching process applied to edge points extracted from the images, the reconstructed points in the scene are clustered using spectral analysis. The obtained clusters are then tracked throughout their center of gravity using a Kalman filter and a Nearest Neighbour (NN) based data association algorithm. The approach is tested and evaluated on real data to demonstrate its effectiveness for obstacle detection and tracking in front of a vehicle. This work is a part of a project that aims to develop advanced driving aid systems, supported by the CPER, STIC and Volubilis programs.

Paper Details

Date Published: 24 January 2011
PDF: 9 pages
Proc. SPIE 7878, Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques, 787806 (24 January 2011); doi: 10.1117/12.876732
Show Author Affiliations
Safaa Moqqaddem, Univ. of Technology of Belfort-Montbéliard (France)
Ibn Tofail Univ. of Kénitra (Morocco)
Y. Ruichek, Univ. of Technology of Belfort-Montbéliard (France)
R. Touahni, Ibn Tofail Univ. of Kénitra (Morocco)
A. Sbihi, Ibn Tofail Univ. of Kénitra (Morocco)


Published in SPIE Proceedings Vol. 7878:
Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques
Juha Röning; David P. Casasent; Ernest L. Hall, Editor(s)

© SPIE. Terms of Use
Back to Top