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Multiple-Sensor Indoor Surveillance System

This paper describes a surveillance system that uses a network of sensors of different kind for localizing and tracking people in an office environment. The sensor network consists of video cameras, infrared tag readers, a fingerprint reader and a PTZ camera. The system implements a Bayesian framewo...

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Main Authors: Petrushin, V.A., Gang Wei, Shakil, O., Roqueiro, D., Gershman, V.
Format: Conference Proceeding
Language:English
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creator Petrushin, V.A.
Gang Wei
Shakil, O.
Roqueiro, D.
Gershman, V.
description This paper describes a surveillance system that uses a network of sensors of different kind for localizing and tracking people in an office environment. The sensor network consists of video cameras, infrared tag readers, a fingerprint reader and a PTZ camera. The system implements a Bayesian framework that uses noisy, but redundant data from multiple sensor streams and incorporates it with the contextual and domain knowledge. The paper describes approaches to camera specification, dynamic background modeling, object modeling and probabilistic inference. The preliminary experimental results are presented and discussed.
doi_str_mv 10.1109/CRV.2006.50
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Cameras
Computerized monitoring
Event detection
Fingerprint recognition
Infrared sensors
Object detection
Robot vision systems
Sensor systems
Surveillance
Working environment noise
title Multiple-Sensor Indoor Surveillance System
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