Vision-Based Preceding Vehicle Detection and Tracking
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Frequency-Tuned Nighttime Brake-Light Detection
IIH-MSP '10 Proceedings of the 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing
On-road vehicle detection using evolutionary Gabor filter optimization
IEEE Transactions on Intelligent Transportation Systems
Hi-index | 0.00 |
This paper presents an improved method for detecting and segmenting taillight pairs of multiple preceding cars in busy traffic in day as well as night. Novelties and advantages of this method are that it is designed to detect multiple car simultaneously, it does not require knowledge of lanes, it works in busy traffic in daylight as well as night, and it is fast irrespective of number of preceding vehicles in the scene, and therefore suitable for real-time applications. The time to process the scene is independent of the size of the vehicle in pixels, and the number of preceding cars detected. One of the previous night taillight detection methods in literature is modified to detect taillight pairs in the scene for both day and night conditions. This paper further introduces a novel hypothesis verification method based on the mathematical relationship between the vehicle distance from the vanishing point and the location of and distance between its taillights. This method enables the detection of multiple preceding vehicles in multiple lanes in a busy traffic environment in real-time. The results are compared with state-of-the-art algorithms for preceding vehicle detection performance, time and ease of implementation.