Machine vision application to automatic intruder detection using CCTV

Hernando Fernandez-Canque, Sorin Hintea, John Freer, Ali Ahmadinia

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)


    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.

    Original languageEnglish
    Title of host publicationProceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems
    ISBN (Print)9783642045912
    Publication statusPublished - 1 Jan 2009


    • CCTV
    • machine vision
    • automatic intruder detection
    • intruder monitoring


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