Integration of control, communication, computation, com- plexity and energy considerations in a coherent design strategy

This report is an overview of the research activities regarding WP06 (C4E co-design) of the FeedNetBack project. The objective of WP6 of Feed- NetBack is to propose a co-design framework, which allows the integration of control-estimation, communication, computation, complexity, and energy considerations in networked control systems. In this report we outline gen- eral guidelines for co-design and illustrate their applicability to the following case studies: (i) surveillance systems using a network of smart cameras and (ii) eets of Autonomous Underwater Vehicles (AUVs).

Re-identificazione per videosorveglianza mediante tecniche di intelligenza artificiale

Nei sistemi di videosorveglianza, un problema aperto \ue8 la re-identificazione automatica di persone, veicoli e altro quando l'oggetto tracciato si sposta tra aree coperte da videocamere diverse, con differenti inquadrature, e cos\uec facendo cambia aspetto. In questo articolo descriviamo un sistema di re-identificazione basato su una rete neurale convoluzionale feed-forward e studiato per re-identificare anche oggetti di classi diverse da quelle sui cui la rete \ue8 stata allenata. Il software per la re-identificazione \ue8 stato implementato sia su personal computer che su una piattaforma embedded utilizzabile in ambito industriale, esibendo anche nel secondo caso tempi di esecuzione accettabili per applicazioni pratiche

Integration of shape constraints in data association filters

Many algorithms have been proposed in literature to deal with the tracking and data association problem. A common assumption made in the proposed algorithms is that the targets are independent. There are however many interesting applications in which targets exhibit some sort of coordination, they satisfy shape constraints. In the current work a general and well formalized method which allows to embed such constraints into data association filters is proposed. The resulting algorithm performs robustly in challenging scenarios

METHOD FOR COORDINATING A PLURALITY OF SENSORS

Method for coordinating a plurality of sensors, wherein a plurality of networked computers control the sensors for the purpose of executing one or more services requested through the network. In order to coordinate with one another, the computers exchange information over the network in a manner such that each networked computer knows the characteristics of and the services executed by the other computers. Subsequently, the computers providing the same service execute the same configuration algorithm that defines the tasks to be carried out by each computer as a function of the characteristics of the computers providing said same service. Thus, the computers get to the same conclusions as to the tasks to be carried out, and control the sensors based on the tasks defined by the configuration algorithm

EVENT DETECTION METHOD AND VIDEO SURVEILLANCE SYSTEM USING SAID METHOD

An event detection method for video surveillance systems and a related video surveillance system are described. The method comprises a learning phase, wherein learning images of a supervised area are acquired at different time instants in the absence of any detectable events, and an operating detection phase wherein current images of said area are acquired. The method detects an event by comparing a current image with an image corresponding to a linear combination of a plurality of reference images approximating, or coinciding with, respective learning images

METHOD AND SYSTEM FOR MONITORING AN ENVIRONMENT

The invention relates to a method for monitoring an environment through a plurality of sensors, wherein a control system receives information from one or more sensors of said plurality and uses said information in order to monitor said environment. The method comprises a setup stage wherein an operator creates a model of an environment by defining a plurality of cells corresponding to areas of said environment, and then creates cell/sensor relationships by defining for each sensor at least one possible position which is associated with at least one cell. For each position the sensor is assigned by the operator a monitoring judgment for the associated cell. The method also comprises an operational stage wherein the control system, in order to perform a surveillance function, finds those sensors which can be used for carrying out the requested surveillance function and controls them based on the monitoring judgments and the cell/sensor relationships

Building a Normality Space of Events - A PCA Approach to Event Detection

The detection of events in video streams is a central task in the automatic vision paradigm, and spans het- erogeneous fields of application from the surveillance of the environment, to the analysis of scientific data. Actually, although well captured by intuition, the definition itself of event is somewhat hazy and depending on the specific application of interest. In this work, the approach to the problem of event detection is different in nature. Instead of defining the event and searching for it within the data, a normality space of the scene is built from a chosen learning sequence The event detection algorithm works by projecting any newly acquired image onto the normality space so as to calculate a distance from it that represents the innovation of the new frame, and defines the metric for triggering an event alert

FeedNetBack-D01.04 - Tool Specifications

FEEDNETBACK deals with problems arising in networked control applications, whose solution requires putting together the instruments of different disciplines, namely control theory, communication and information theory, and computer science. Each of these disciplines has its own characteristics in terms of problems that are typically faced, and in terms of the requirements which are typically desirable in the systems to be designed. Therefore, it is necessary to integrate in a software different functionalities in order to simulate correctly the behavior of the whole set. This deliverable focuses on the different tool specifications which are proper in the simulators of each of these disciplines and significant in the class of problems considered in the present project. In this way, we first present a survey on available tools for each of these disciplines, in which we analyze the functionalities than can be used to simulate the behavior of networked control systems. Next, we explore how existing tools can be combined in order to provide different functionalities with good results. After this overview, we present a discussion about the guidelines for determining the tools functionalities related to control, communication and computation which make sense in networked control systems. Especially we focus on the case studies developed in work packages WP7 and WP8, respectively Smart camera networks for surveillance and motion capture and Application to underwater exploration by multi-agent systems. Finally, we determine the functionalities and specifications that will serve as guidelines for the tool development efforts of work packages WP2-5. This report presents the functionalities and specifications of the computational tools that enable the simulation of networked control systems, and thus, the application of theoretical results. This document is an input to WP2-5 where the described tool set will be developed.

FeedNetBack-D01.04 - Tool Specifications

FEEDNETBACK deals with problems arising in networked control applications, whose solution requires putting together the instruments of different disciplines, namely control theory, communication and information theory, and computer science. Each of these disciplines has its own characteristics in terms of problems that are typically faced, and in terms of the requirements which are typically desirable in the systems to be designed. Therefore, it is necessary to integrate in a software different functionalities in order to simulate correctly the behavior of the whole set. This deliverable focuses on the different tool specifications which are proper in the simulators of each of these disciplines and significant in the class of problems considered in the present project. In this way, we first present a survey on available tools for each of these disciplines, in which we analyze the functionalities than can be used to simulate the behavior of networked control systems. Next, we explore how existing tools can be combined in order to provide different functionalities with good results. After this overview, we present a discussion about the guidelines for determining the tools functionalities related to control, communication and computation which make sense in networked control systems. Especially we focus on the case studies developed in work packages WP7 and WP8, respectively Smart camera networks for surveillance and motion capture and Application to underwater exploration by multi-agent systems. Finally, we determine the functionalities and specifications that will serve as guidelines for the tool development efforts of work packages WP2-5. This report presents the functionalities and specifications of the computational tools that enable the simulation of networked control systems, and thus, the application of theoretical results. This document is an input to WP2-5 where the described tool set will be developed.

Integration of control, communication, computation, com- plexity and energy considerations in a coherent design strategy

This report is an overview of the research activities regarding WP06 (C4E co-design) of the FeedNetBack project. The objective of WP6 of Feed- NetBack is to propose a co-design framework, which allows the integration of control-estimation, communication, computation, complexity, and energy considerations in networked control systems. In this report we outline gen- eral guidelines for co-design and illustrate their applicability to the following case studies: (i) surveillance systems using a network of smart cameras and (ii) eets of Autonomous Underwater Vehicles (AUVs).