Andrea Pennisi

Learn More
Maritime environment represents a challenging scenario for automatic video surveillance due to the complexity of the observed scene: waves on the water surface, boat wakes, and weather issues contribute to generate a highly dynamic background. Moreover, an appropriate background model has to deal with gradual and sudden illumination changes, camera jitter,(More)
Today’s robots are able to perform more and more complex tasks, which usually require a high degree of interaction with the environment they have to operate in. As a consequence, robotic systems should have a deep and specific knowledge of their workspaces, which goes far beyond a simple metric representation a robotic system can build up through SLAM(More)
Automatically detecting events in crowded scenes is a challenging task in Computer Vision. A number of offline approaches have been proposed for solving the problem of crowd behavior detection, however the offline assumption limits their application in real-world video surveillance systems. In this paper, we propose an online and real-time method for(More)
In this paper an open source software for monitoring humanoid soccer robot behaviours is presented. The software is part of an easy to set up system, conceived for registering ground truth data that can be used for evaluating and testing methods such as robot coordination and localization. The hardware architecture of the system is designed for using(More)
Detection, tracking, and classification of people and vehicles are fundamental processes in intelligent surveillance systems. The use of publicly available data set is the appropriate way to compare the relative merits of existing methods and to develop and assess new robust solutions. In this paper, we focus on the maritime domain and we describe the(More)
Automatic surveillance of public areas, such as airports, train stations, and shopping malls, requires the capacity of detecting and recognizing possible abnormal situations in populated environments. In this book chapter, an architecture for intelligent surveillance in indoor public spaces, based on an integration of interactive and non-interactive(More)
Developing automatic diagnostic tools for the early detection of skin cancer lesions in dermoscopic images can help to reduce melanoma-induced mortality. Image segmentation is a key step in the automated skin lesion diagnosis pipeline. In this paper, a fast and fully-automatic algorithm for skin lesion segmentation in dermoscopic images is presented.(More)
Automatic surveillance systems for the maritime domain are becoming more and more important due to a constant increase of naval traffic and to the simultaneous reduction of crews on decks. However, available technology still provides only a limited support to this kind of applications. In this paper, a modular system for intelligent maritime surveillance,(More)
Background modeling in fast changing scenarios is a challenging task due to unexpected events like sudden illumination changes, reflections, and shadows, which can strongly affect the accuracy of the foreground detection. In this paper, we describe a real-time and effective background modeling approach, called FAFEX, that can deal with global and rapid(More)