@article{ref1,
title="A vision-based approach to collision prediction at traffic intersections",
journal="IEEE transactions on intelligent transportation systems",
year="2005",
author="Atev, S. and Arumugam, H. and Masoud, O. and Janardan, R. and Papanikolopoulos, N.p.",
volume="6",
number="4",
pages="416-423",
abstract="Monitoring traffic intersections in real time and predicting possible collisions is an important first step towards building an early collision-warning system. We present a vision-based system addressing this problem and describe the practical adaptations necessary to achieve real-time performance. Innovative low-overhead collision-prediction algorithms (such as the one using the time-as-axis paradigm) are presented. The proposed system was able to perform successfully in real time on videos of quarter-video graphics array (VGA) (320 times; 240) resolution under various weather conditions. The errors in target position and dimension estimates in a test video sequence are quantified and several experimental results are presented.<p />",
language="",
issn="1524-9050",
doi="10.1109/TITS.2005.858786",
url="http://dx.doi.org/10.1109/TITS.2005.858786"
}