CRIS Current Research Information System
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishTo enhance video surveillance systems, multi-modal sensor integration can be a successful strategy. In this work, a computer vision system able to detect and track people from multiple cameras is integrated with a wireless sensor network mounting PIR (Passive InfraRed) sensors. The two subsystems are briefly described and possible cases in which computer vision algorithms are likely to fail are discussed. Then, simple but reliable outputs from the PIR sensor nodes are exploited to improve the accuracy of the vision system. In particular, two case studies are reported: the first uses the presence detection of PIR sensors to disambiguate between an opened door and a moving person, while the second handles motion direction changes during occlusions. Preliminary results are reported and demonstrate the usefulness of the integration of the two subsystems.
| Titolo: | An Integrated MultiModal Sensor Network for Video Surveillance | |
| Autore/i: | Andrea Prati; Roberto Vezzani; BENINI, LUCA; FARELLA, ELISABETTA; ZAPPI, PIERO | |
| Autore/i Unibo: | ||
| Anno: | 2005 | |
| Titolo del libro: | Proceedings of the 3rd ACM International Workshop on Video Surveillance & Sensor Networks (VSSN05) | |
| Pagina iniziale: | 95 | |
| Pagina finale: | 102 | |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1145/1099396.1099415 | |
| Abstract: | To enhance video surveillance systems, multi-modal sensor integration can be a successful strategy. In this work, a computer vision system able to detect and track people from multiple cameras is integrated with a wireless sensor network mounting PIR (Passive InfraRed) sensors. The two subsystems are briefly described and possible cases in which computer vision algorithms are likely to fail are discussed. Then, simple but reliable outputs from the PIR sensor nodes are exploited to improve the accuracy of the vision system. In particular, two case studies are reported: the first uses the presence detection of PIR sensors to disambiguate between an opened door and a moving person, while the second handles motion direction changes during occlusions. Preliminary results are reported and demonstrate the usefulness of the integration of the two subsystems. | |
| Data prodotto definitivo in UGOV: | 27-giu-2013 | |
| Appare nelle tipologie: | 4.01 Contributo in Atti di convegno |
File in questo prodotto:
Copyright © 2021