FAST – Sobel realtime low level feature extraction with a surveillance camera

FAST – Sobel realtime low level feature extraction with a surveillance camera

The growing mobility of people and goods has a very high societal cost in terms of traffic congestion and of fatalities and injured people every year. The management of a road network needs efficient ways for assessment at minimal costs.

Road monitoring is a relevant part of road management, especially for safety, optimal traffic flow and for investigating new sustainable transport patterns. Current monitoring systems based on video lack of optimal usage of networks and are difficult to be extended efficiently.

The ORUSSI project focuses on road monitoring through a network of roadside sensors (mainly cameras) that can be dynamically deployed and added to the surveillance systems in an efficient way.

The main objective of the project is to develop an optimized platform offering innovative real-time media (video and data) applications for road monitoring in real scenarios. We exploit low-level efficient image features in order to enable our distributed system to extract semantic information from the imagery and to optimize the video compression adaptively.