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— The emergence of new wearable technologies, such as action cameras and smart glasses, has increased the interest of computer vision scientists in the first person perspective. Nowadays, this field is attracting attention and investments of companies aiming to develop commercial devices with first person vision (FPV) recording capabilities. Due to this(More)
—The employment of sophisticated tools for data analysis in distributed or structurally complex systems requires the development of specific architectures and data fusion strategies in order to integrate heterogeneous information coming from the environmental sensors. Recently, intelligent sensor networks have been widely deployed for various purposes(More)
—The emergence of new pervasive wearable technologies (e.g. action cameras and smart glasses) calls attention to the so called First Person Vision (FPV). In the future, more and more everyday-life videos will be shot from a first-person point of view, overturning the classical fixed-camera understanding of Vision, specializing the existing knowledge of(More)
—Intelligent camera networks have been lately employed for a wide range of heterogeneous purposes, concerning both security and safety oriented systems. Military and civil applications ranging from border surveillance and public spaces monitoring to ambient intelligence and road safety are representative of such various applications. In this paper a(More)
Cognitive algorithms, integrated in intelligent systems, represent an important innovation in designing interactive smart environments. More in details, Cognitive Systems have important applications in anomaly detection and management in advanced video surveillance. These algorithms mainly address the problem of modelling interactions and behaviours among(More)
This work addresses the problem of people counting in crowded situations, such as urban environments, in computer vision. As crowding density increases in a scene, it might become impossible to count people as single individuals: a global group-based approach is then preferable and in fact often necessary. A simple method for estimating the count of people(More)
In most recent Intelligent Video Surveillance systems, mechanisms to support human decisions are integrated in cognitive artificial processes. These algorithms mainly address the problem of extraction and modelling of relevant information from a sensor network. In crowd monitoring the main problem is to individuate specific events as for example different(More)
First Person Vision (Egocentric) video analysis stands nowadays as one of the emerging fields in computer vision. The availability of wearable devices recording exactly what the user is looking at is ineluctable and the opportunities and challenges carried by this kind of devices are broad. Particularly, for the first time a device is so intimate with the(More)
—In this work, we propose a strategy for optimizing a superpixel algorithm for video signals, in order to get closer to real time performances which are on the one hand needed for egocentric vision applications and on the other must be bearable by wearable technologies. Instead of applying the algorithm frame by frame, we propose a technique inspired to(More)
—Human behaviour analysis has important applications in the field of anomaly management, such as Intelligent Video Surveillance (IVS). As the number of individuals in a scene increases, however, new macroscopic complex behaviours emerge from the underlying interaction network among multiple agents. This phenomenon has lately been investigated by modelling(More)