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The paper presents a real-time vision system for automatic traffic monitoring based on a network of autonomous tracking units that capture and process images from one or more pre-calibrated cameras. The system, which has been developed within the framework of TRAVIS (TRAffic VISual monitoring) project, is flexible, scalable and can be useable for a broad field of applications, including traffic monitoring of tunnels at highways and aircraft parking areas at airports. Different image processing and data fusion techniques were tested and evaluated in order to be incorporated to the system. The final output of the image processing is a set of information for each moving object in the scene, such as target ID, position, velocity and classification. This can be transmitted to a remote traffic control centre, as the network demands are remarkably low. This information is analyzed and used to provide real-time output (e.g. alerts, electronic road signs, ramp meters, etc) as well as to extract useful statistical information (traffic loads, lane changes, average velocity etc).