Robust background subtraction using data fusion for real elevator scene

Taeyup Song, David K. Han, Hanseok Ko

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

    4 Citations (Scopus)

    Abstract

    This paper proposes a background subtraction technique robust in elevator environments. Sudden local illumination changes arise frequently in an elevator environment due to opening and closing of the elevator door as well as the inner walls of elevator being made of reflective materials. We present a novel method sequentially fusing a Gaussian mixture model for background subtraction, motion information and a spatial likelihood model based on textured features. Experimental results on real video data demonstrate effectiveness of the proposed approach.

    Original languageEnglish
    Title of host publication2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2011
    Pages392-397
    Number of pages6
    DOIs
    Publication statusPublished - 2011
    Event2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2011 - Klagenfurt, Austria
    Duration: 2011 Aug 302011 Sept 2

    Publication series

    Name2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2011

    Other

    Other2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2011
    Country/TerritoryAustria
    CityKlagenfurt
    Period11/8/3011/9/2

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Signal Processing

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