A Unified Approach for On-Road Visual Night-time Vehicle Light Detection (CROSBI ID 620104)
Prilog sa skupa u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Jurić Darko ; Lončarić Sven
engleski
A Unified Approach for On-Road Visual Night-time Vehicle Light Detection
Traffic accidents are more frequent during night- time despite lower traffic volume. Driver assistance systems can increase car and road safety. Such systems are often visual based, where the base is vehicle light detection. A method for night-time vehicle light detection is presented which is capable to detect front and rear vehicle lights. The detection procedure operates on raw pixels, which does not need extensive image pre- processing such as image segmentation thus improving robustness and performance. Although two classes of vehicle lights are detected, a single binary classifier architecture is used to detect all categories of vehicles lights. The obtained detections are then labeled by using the same approach. The result is a simple yet effective architecture capable to detect vehicle lights in various night-time lighting conditions.
headlight-detection ; rear-light classification ; object detection ; nighttime-vehicle-detection
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Podaci o prilogu
730-740.
2014.
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objavljeno
Podaci o matičnoj publikaciji
Lecture notes in computer science
Bebis George
Las Vegas (NV): Springer
0302-9743
Podaci o skupu
10th International Symposium on Visual Computing
predavanje
08.12.2014-10.12.2014
Las Vegas (NV), Sjedinjene Američke Države