A Two-Layer Night-Time Vehicle Detector

We present a two-layer night time vehicle detector in this work. At the first layer, vehicle headlight detection is applied to find areas (bounding boxes) where the possible pairs of headlights locate in the image, the Haar feature based AdaBoost framework is then applied to detect the vehicle front...

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Bibliographic Details
Published in2009 Digital Image Computing: Techniques and Applications pp. 162 - 167
Main Authors Weihong Wang, Chunhua Shen, Jian Zhang, Paisitkriangkrai, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2009
Subjects
Adaboost
Cameras
Detectors
Filters
headlight detector
Merging
Object detection
Pixel
Subtraction techniques
Traffic control
Vehicle detection
Vehicles
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Summary:We present a two-layer night time vehicle detector in this work. At the first layer, vehicle headlight detection is applied to find areas (bounding boxes) where the possible pairs of headlights locate in the image, the Haar feature based AdaBoost framework is then applied to detect the vehicle front. This approach has achieved a very promising performance for vehicle detection at night time. Our results show that the proposed algorithm can obtain a detection rate of over 90% at a very low false positive rate (1.5%). Without any code optimization, it also performs at a faster speed compared to the standard Haar feature based AdaBoost approach.
ISBN:142445297X
9781424452972
DOI:10.1109/DICTA.2009.33