Implementation of Vehicle Detection and Tracking Model Using YOLO and DeepSORT for Controlling Traffic Rule Violation

Abstract

The field of computer vision has advanced significantly in the last several years, especially in the areas of object tracking and detection. This research offers a thorough analysis of the use of a vehicle tracking and detection model that makes use of DeepSORT (Deep Simple Online and Realtime Tracking) for tracking and YOLOv8 (You Only Look Once version 8) for detection. By combining these state-of-the-art methods, it will be possible to track and identify vehicles in a variety of situations in real-time, improving surveillance and traffic management as well as autonomous vehicle navigation. This project intends to develop computer vision applications in the transportation and surveillance sectors by means of a thorough examination and experimentation.