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A vision-based approach to collision prediction at traffic intersections

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5 Author(s)
Atev, S. ; Dept. of Comput. Sci. & Eng., Univ. of Minnesota, Minneapolis, MN, USA ; Arumugam, H. ; Masoud, O. ; Janardan, R.
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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 × 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.

Published in:

Intelligent Transportation Systems, IEEE Transactions on  (Volume:6 ,  Issue: 4 )