Traffic surveillance is an important topic in computer vision and intelligent transportation systems and has intensively been studied in the past decades. However, most of the state-of-the-art methods concentrate on daytime traffic monitoring. In this paper, we propose a nighttime traffic surveillance system, which consists of headlight detection, headlight tracking and pairing, and camera calibration and vehicle speed estimation. First, a vehicle headlight is detected using a reflection intensity map and a reflection suppressed map based on the analysis of the light attenuation model. Second, the headlight is tracked and paired by utilizing a simple yet effective bidirectional reasoning algorithm. Finally, the trajectories of the vehicle's headlight are employed to calibrate the surveillance camera and estimate the vehicle's speed. Experimental results on typical sequences show that the proposed method can robustly detect, track, and pair the vehicle headlight in night scenes. Extensive quantitative evaluations and related comparisons demonstrate that the proposed method outperforms state-of-the-art methods.
Tracking and Pairing Vehicle Headlight in Night Scenes
IEEE Transactions on Intelligent Transportation Systems ; 13 , 1 ; 140-153
2012-03-01
1992658 byte
Article (Journal)
Electronic Resource
English
Tracking and Pairing Vehicle Headlight in Night Scenes
Online Contents | 2012
|Headlight hints for night driving
Engineering Index Backfile | 1928