Semantic Modeling and Acquisition for Urban Safety Simulations

General Information

This project aims at analysing the traffic flow of open roads in real time by a sensor fusion of radar data with video feeds. Radar gives an accurate position and velocity of vehicles making computer vision methods more robust in computing their spatial extent and classification from video streams. In this way the huge amount of raw data is reduced to semantically relevant information, which is highly memory efficient, anonymous and sufficient to reconstruct traffic flow over long time periods. Another important goal is a sophisticated 3D visualization of the reconstructed traffic flow providing interactive tools for visual analysis. Information obtained in this way will significantly contribute in adopting measures to increase traffic safety.

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