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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Machine Vision Application to Automatic Intruder Detection Using CCTV
verfasst von : Hernando Fernandez-Canque, Sorin Hintea, John Freer, Ali Ahmadinia
Erschienen in: Knowledge-Based and Intelligent Information and Engineering Systems
Verlag: Springer Berlin Heidelberg
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The work presented in this paper addresses the application of new technologies to the task of intruder monitoring. It presents an innovative Machine Vision application to detect and track a person in a Closed Circuit Television System (CCTV) identifying suspicious activity. Neural Network techniques are applied to identify suspicious activities from the trajectory path, speed, direction and risk areas for a person in a scene, as well as human posture. Results correlate well with operator determining suspicious activity. The automated system presented assists an operator to increase reliability and to monitor large numbers of surveillance cameras.