Object Detection Framework for High Mobility Vehicles Tracking in Night-Time

Optical Vehicular Communication is one of the most promising areas in which Optical Camera Communication (OCC) involves as the core technology. Due to a lot of existing challenges in Optical Vehicular Communication, there is still a big gap between research works and commercialized products. Recent developments in computer vision and advanced image processing techniques could enhance the performance of vehicular OCC system significantly. Among those techniques, there are many of robust image processing tools which are developed based on the theory of Machine Learning, Deep Learning and Artificial Intelligence (AI), which could be applied in a wide range of applications including vehicular OCC application. In this paper, we would like to introduce our recent work on applying a well-known object detection framework - You Only Look Once (YOLO) to detect and track a large number of high mobility vehicles, which is also considered as region of interests (RoIs) in vehicular OCC system. From that, we conducted a test on the Korea highway at a raining night to analyze the effectiveness of this method in the vehicular OCC system.