Vehicle Classification and Counting for Traffic Video Monitoring Using YOLO-v3

Traffic has been a major concern in most of the cities. Monitoring cameras are used to track, detect and count vehicles in real-time to ensure proper management of traffic. Counting of vehicles like cars, trucks and two wheelers is important for Intelligent Transportation System (ITS) to identify the intensity of traffic flow. In this paper we proposed vision based vehicle classification and counting approach using YOLO- v3 framework. The proposed method is composed of steps like masking, detection, classification and counting of different classes of vehicles. We have tested proposed method over 2000 vehicles of different categories obtained from the CCTV camera installed at main gate of lIT Patna campus. Experimental results show that the proposed approach has achieved accuracy of 93.65 % and 87.68 % during daytime and nighttime respectively.