2011 chapter
Detection of Multiple Preceding Cars in Busy Traffic Using Taillights
In Lecture Notes in Computer Science (pp. 338–347).
TL;DR:
An improved method for detecting and segmenting taillight pairs of multiple preceding cars in busy traffic in day as well as night and 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 are introduced.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
11. Sustainable Cities and Communities
(OpenAlex)
Source: ORCID
Added: July 1, 2022
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.