1,720,977 research outputs found
Distribution of intelligence and configurability in wireless surveillance networks
No full textThis work1 considers the distributed decomposition of the image processing tasks in wireless video-based surveillance networks. We considered the use of a Spread Spectrum-based wireless radio link, dynamically configurable by means of software radio technology, for remote transmission of the visual information from the peripheral sensor level to the central operator level. The considered video-based surveillance application is related to an image processing system for people counting. The distribution of the image processing tasks is performed by embedding at the sensor level some low-level image processing modules. The results obtained by the distributed architecture in terms of counting precision, are then compared with the ones provided by a centralised architecture performing the overall image processing tasks at the operator level, considering in both cases different configurations of the radio link in terms of spreading factor
Performance evaluation of MC-CDMA techniques for variable bit-rate transmission in LEO satellite networks
No full textThis work is aimed at investigating the use of Multi-Carrier CDMA (MC-CDMA) techniques in variable bit-rate transmission over low-earth-orbit (LEO) satellite channels by means of realistic simulations. It is known by literature that MC-CDMA techniques are much more resilient with respect to multi-user interference effects in multipath fading channels than single-carrier DS/CDMA ones. Moreover, MC-CDMA exhibits a natural capability to deliver multirate services simply by assigning to each user a variable-cardinality set of subcarriers. The achieved simulation results clearly confirmed the expected improved robustness of MC-CDMA techniques transmitting multirate data streams in frequency selective LEO satellite channels, with respect to state-of-the-art DS/CDMA transceivers
Adaptive change detection approach for object detection in outdoor scenes under variable speed illumination changes
No full textIn this paper an adaptive algorithm is presented for the detection of changes in outdoor video-surveillance images. The proposed method can be considered as basis for a low level image processing stage in a advanced video-surveillance system. The main feature of the algorithm is the robustness to the illumination changes in the scene: this robustness is achieved by using a background updating module working in cooperation with the change detection algorithm. The background updating method works in a different way according to speed of illumination changes. If a sudden illumination change is detected the background is heavily updated while if a slow lightning variation occurs, a continuous soft updating module is used to take into account the long-term slow illumination changes. Experimental results of an automatic people counting system including the proposed low level image processing stage indicate that the method detects changes accurately in case of time-varying illumination
"Use of intelligent sensors and software radio technologies for optimal design of reconfigurable multimedia surveillance networks"
No full textNeural Network-Based Techniques for Efficient Detection of Variable-Bit-Rate Signals in MC-CDMA Systems Working over LEO Satellite Networks
No full text“Optimization of coarse synchronisation performances by non-linear signal pre-processing of GNSS signals in RADAR jammed environments”
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Use of Neural Networks for Behavior Understanding in Railway Transport Monitoring Applications
No full text“Integrazione di sistemi di navigazione satellitare e comunicazioni cellulari tramite tecniche basate su software radio”
No full textUse of neural networks for behaviour understanding in railway transport monitoring applications
No full textIn the last years, the interest for advanced video-based surveillance applications is more and more growing. This is especially true in the field of railway urban transport where video-based surveillance can be exploited to face many relevant security aspects (e.g. vandal acts, overcrowding situations, abandoned object detection, etc.). This paper aims at investigating an open problem in the implementation of video-based surveillance systems for transport applications, i.e.: the implementation of reliable image understanding modules in order to recognize dangerous situations with reduced false alarm and misdetection rates. In this work, we considered the use of a neural network-based classifier for detecting vandal behaviors in metro stations. The achieved results show that the classifier choice mentioned above allows one to achieve very good performances also in presence of high scene complexity
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