Learn More
Background subtraction is a widely used operation in the video surveillance, aimed at separating the expected scene (the background) from the unexpected entities (the foreground). There are several problems related to this task, mainly due to the blurred boundaries between background and foreground definitions. Therefore, background subtraction is an open(More)
Human Robot Interaction is a key enabling feature to support the introduction of robots in everyday environments. However, robots are currently incapable of building representations of the environments that allow both for the execution of complex tasks and for an easy interaction with the user requesting them. In this paper, we focus on semantic mapping,(More)
Visual surveillance in dynamic scenes is currently one of the most active research topics in computer vision and many existing applications are available. However, difficulties in realizing effective video surveillance systems that are robust to the many different conditions that arise in real environments, make the actual deployment of such systems very(More)
In this paper we describe a system for boat traffic monitoring that has been realized for analyzing and computing statistics of trafic in the Grand Canal in Venice. The system is based on a set of survey cells to monitor about 6 Km of canal. Each survey cell contains three cameras oriented in three directions and covering about 250-300 meters of the canal.(More)
Visual tracking of multiple targets is a key step in surveillance scenarios, far from being solved due to its intrinsic ill-posed nature. In this paper, a comparison of Multi-Hypothesis Kalman Filter and Particle Filter-based tracking is presented. Both methods receive input from a novel online background subtraction algorithm. The aim of this work is to(More)