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

3 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 Sep 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
CountryAustria
CityKlagenfurt
Period11/8/3011/9/2

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

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  • Cite this

    Song, T., Han, D. K., & Ko, H. (2011). Robust background subtraction using data fusion for real elevator scene. In 2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2011 (pp. 392-397). [6027357] (2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2011). https://doi.org/10.1109/AVSS.2011.6027357