24 December 2013 Unattended vehicle detection for automatic traffic light control
Author Affiliations +
Proceedings Volume 9067, Sixth International Conference on Machine Vision (ICMV 2013); 90670W (2013) https://doi.org/10.1117/12.2050938
Event: Sixth International Conference on Machine Vision (ICMV 13), 2013, London, United Kingdom
Abstract
Machine vision based traffic light control depends mainly on measuring traffic statistics at cross roads. Most of the previous studies have not taken unattended vehicles into consideration when calculating either the traffic density or the traffic flow. In this paper, we propose incorporating unattended vehicles into a new metric for measuring the traffic congestion. In addition to the vehicle motion analysis, opening the driver's side door is an important indicator that this vehicle is going to be unattended. Therefore, we focus in this paper on presenting how to detect this event for stationary vehicles from a live camera or a video feed. Through a set of experiments, we have found out that a Scale Invariant Feature Transform (SIFT) feature-descriptor with a Support Vector Machines (SVM) classifier was able to successfully classify open-door vehicles from closed-door ones in 96.7% of our test dataset.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Aya Salama Abdel Hady, Mohamed Moustafa, "Unattended vehicle detection for automatic traffic light control", Proc. SPIE 9067, Sixth International Conference on Machine Vision (ICMV 2013), 90670W (24 December 2013); doi: 10.1117/12.2050938; https://doi.org/10.1117/12.2050938
PROCEEDINGS
5 PAGES


SHARE
Back to Top