Night Time Vehicle Detection
Night driving is one of the major factors which affects traffic safety. Although detecting oncoming vehicles at night time is a challenging task, it may improve traffic safety. If the oncoming vehicle is recognised in good time, this will motivate drivers to keep their eyes on the road. The purpose...
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Veröffentlicht in: | Journal of intelligent systems 2012-07, Vol.21 (2), p.143-165 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Night driving is one of the major factors which affects traffic safety.
Although detecting oncoming vehicles at night time is a challenging task, it
may improve traffic safety. If the oncoming vehicle is recognised in good
time, this will motivate drivers to keep their eyes on the road. The purpose
of this paper is to present an approach to detect vehicles at night based on
the employment of a single onboard camera. This system is based on detecting
vehicle headlights by recognising their shapes via an SVM classifier which
was trained for this purpose. A pairing algorithm was designed to pair
vehicle headlights to ensure that the two headlights belong to the same
vehicle. A multi-object tracking algorithm was invoked to track the vehicle
throughout the time the vehicle is in the scene. The system was trained with
503 single objects and tested using 144 587 single objects which were
extracted from 1410 frames collected from 15 videos and 27 moving vehicles.
It was found that the accuracy of recognition was 97.9% and the vehicle
recognition rate was 96.3% which indicates clearly the high robustness
attained by this system. |
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ISSN: | 0334-1860 2191-026X 2191-026X |
DOI: | 10.1515/jisys-2012-0007 |