Real-Time Moving Vehicle Detection, Tracking, and Counting System Implemented with CVZone

Abstract

Real-time vehicle detection, tracking, and counting systems play a crucial role in intelligent transportation systems (ITS). These systems help in traffic monitoring, congestion management, and road safety. This paper presents an approach leveraging CVZone, an open-source computer vision library built on OpenCV and MediaPipe, to implement an efficient and accurate system for detecting, tracking, and counting vehicles in real time. The proposed method utilizes deep learning-based object detection models to identify vehicles, optical flow techniques for tracking, and computationally optimized counting mechanisms. We discuss the challenges encountered during development, evaluate the system’s performance, and explore future improvements and trends in the field.

DOI - https://doi.org/10.65525/SVUP.9788199651517.2026.136-139