Real Time Vehicle Tracking using YOLO Algorithm

Abstract

In this research work, we aim to implement a real-time vehicle-detecting system using the YOLO algorithm. The system processes images and videos to identify the region of interest and detect vehicles using various techniques. The detected vehicles are then classified into different categories such as cars, trucks, and buses using DNN models. The system also tracks the movement of vehicles across consecutive frames of video to count the total number of vehicles passing through a given area. The final results are displayed in a graphical user interface, providing an easy-to-use interface for users. This research has potential applications in traffic management, surveillance, and security systems.