this progrrame is a real-time car tracking program that utilizes computer vision techniques to detect and track cars in live video streams. This program is designed to accurately identify and follow the movement of cars in real time, providing valuable information for various applications such as traffic monitoring, surveillance, or autonomous driving.
note : you will find also the article (wrote by me) that explain all the technique used in the project , also ppt format (feel free to use them in your project
The key features of my car tracking program include:
The program uses state-of-the-art object detection models, such as YOLO or SSD, to detect cars in each frame of the live video stream. This ensures efficient and accurate detection of cars in real time.
Once the cars are detected, a robust object tracking algorithm is employed to track their movement across consecutive video frames. The tracking algorithm utilizes techniques such as optical flow, Kalman filters, or correlation-based methods to estimate and predict the position of the tracked cars.
The program can track multiple cars simultaneously, allowing for the monitoring of multiple vehicles within the video stream. Each tracked car is assigned a unique identifier, enabling individual tracking and analysis.
The program provides real-time visualization of the tracked cars, displaying bounding boxes around the detected cars and their trajectories on the video stream. This visual feedback enhances the monitoring and analysis of the car movement.
To ensure real-time performance, the program leverages hardware acceleration techniques, such as GPU processing, to speed up the object detection and tracking processes. This enables efficient processing of high-resolution video streams in real time.
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