The goal is to monitor the traffic of passing vehicles within an area of interest (e.g. highway) through the installation of a set of cameras and other types of sensors (e.g. radar) capable of observing the area from different viewpoints and with partially overlapping fields of view.
The system needs to integrate information from multiple viewpoints and be able to detect all vehicles in the area of interest in real time, classify them, accurately locate them and track their movement. There is also the need to synchronize video streams, calibrate different viewpoints, and manage occlusions, all in real time.
We integrated artificial intelligence and computational vision techniques for vehicle recognition and classification with multi-target tracking, stochastic filtering, and data fusion techniques for vehicle tracking.
Results and Benefits
Intervention methods enable effective vehicle identification.