Road traffic monitoring system

This work proposes a framework for road traffic surveillance using computer vision techniques. After a foreground estimation, post processing techniques are applied to the detected vehicles in motion to generate blobs. Then, a tracking approach based on Kalman filters is used to extract instantaneous information throughout a video sequence, including speed and trajectory estimation and imprudent driving detection. The system has been developed in Python and can be launched in real-time using a standard CPU.

For more information see the report and slides.