On the Fly Vehicle Modeling and Tracking with 2D-LiDAR Detector and Infrared Camera

Kazuhiko Sumi, Kazunari Takagi, Tatsuya Oshiro, Takuya Matsumoto, Kazuyoshi Kitajima, Yoshifumi Hayakawa, Masayuki Yamamoto

Abstract: We propose a vehicle detection and tracking system that tracks vehicles from the rear using a 10-band infrared (IR) surveillance camera installed along the expressway. The main reason for using an infrared camera is to suppress the strong light reflections of head and tail lights of the vehicle at rainy night. However, due to lack of a large IR traffic video datasets covering all type of vehicles, we will not be able to take advantages of recent machine learning advances. Therefore, we propose rather straight approach to detect vehicles by a pair of 2D-LiDARs, then generate the image model of vehicle to be tracked on the fly. We prototyped the system and evaluated it with a normal traffic video taken on a highway. We achieved a 94% tracking success rate at a distance of 20m to 70m from the camera and mean error of localization is less than 2m at 70m.