MORERIO , Pietro

No description

Main drawbacks in single-camera multi-target visual tracking can be partially removed by increasing the amount of information gathered on the scene, i.e. by adding cameras. By adopting such a multi-camera approach, multiple sensors cooperate for overall scene understanding. However, new issues arise such as data association and data...

Superpixel methods have become popular in recent years as they provide an efficient preprocessing tool for a manifold of computer vision applications. In this work, we propose a method based on a self-adapting and self-growing network, which is bred starting from two random initialization seeds in the image. Such a network, which is a...

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...

This work addresses the issue of fire and smoke detection in a scene within a video surveillance framework. Detection of fire and smoke pixels is at first achieved by means of a motion detection algorithm. In addition, separation of smoke and fire pixels using colour information (within appropriate spaces, specifically chosen in order to...

No description

Recently, a Bayesian estimator with a hybrid update was developed [1], based on a mathematical formulation of sampling. Such an Event Based State Estimator (EBSE) allows for a stable synchronous state estimate, relying on asynchronous measurements. Usefulness of such a filter comes with its approximate analytic formulation, which is attainable...

Abstract—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...

Human behavior analysis for Cognitive Surveillance Systems (CSS) share mainly the concept that it can be time to extend functionalities beyond simple video analytics. In most recent systems addressed by research, automatic support to human decisions based on object detection, tracking and situation assessment tools is integrated as a part of a...

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...

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...

Under a tracking framework, the definition of the target state is the basic step for automatic understanding of dynamic scenes. More specifically, far object tracking raises challenges related to the potentially abrupt size changes of the targets as they approach the sensor. If not handled, size changes can introduce heavy issues in data...

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...

This work addresses the issue of fire and smoke detection in a scene within a video surveillance framework. Detection of fire and smoke pixels is at first achieved by means of a motion detection algorithm. In addition, separation of smoke and fire pixels using colour information (within appropriate spaces, specifically chosen in order to...

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...

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 recording capabilities. Due to this...

Main drawbacks in single-camera multi-target visual tracking can be partially removed by increasing the amount of information gathered on the scene, i.e. by adding cameras. By adopting such a multi-camera approach, multiple sensors cooperate for overall scene understanding. However, new issues arise such as data association and data fusion....

Classifying frames, or parts of them, is a common way of carrying out detection tasks in computer vision. However, frame by frame classification suffers from sudden significant variations in image texture, colour and luminosity, resulting in noise in the extracted features and consequently in the decisions taken. Support Vector Machines have...

Abstract—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...