Linear stereo vision based objects detection and tracking using spectral clustering

Safaa Moqqaddem; Y. Ruichek; R. Touahni; A. Sbihi

doi:10.1117/12.876732

24 January 2011 Linear stereo vision based objects detection and tracking using spectral clustering

Safaa Moqqaddem, Y. Ruichek, R. Touahni, A. Sbihi

Proceedings Volume 7878, Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques; 787806 (2011) https://doi.org/10.1117/12.876732
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

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.

Citation Download Citation

Safaa Moqqaddem, Y. Ruichek, R. Touahni, and A. Sbihi "Linear stereo vision based objects detection and tracking using spectral clustering", Proc. SPIE 7878, Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques, 787806 (24 January 2011); https://doi.org/10.1117/12.876732

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