Robust environmental change detection using PTZ camera via spatial-temporal probabilistic modeling

Jwu-Sheng Hu*, Tzung Min Su

*Corresponding author for this work

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

This paper proposes a novel procedure for detecting environmental changes by using a pan-tilt-zoom (PTZ) camera. Conventional approaches based on pixel space and stationary cameras need time-consuming image registration to yield pixel statistics. This work proposes an alternative approach to describe each scene with a Gaussian mixture model (GMM) via a spatial-temporal statistical method. Although details of the environment covered by the camera are lost, this model is efficient and robust in recognizing scene and detecting scene changes in the environment. Moreover, the threshold selection for separating different environmental changes is convenient by using the proposed framework. The effectiveness of the proposed method is demonstrated experimentally in an office environment.

Original languageEnglish
Pages (from-to)339-344
Number of pages6
JournalIEEE/ASME Transactions on Mechatronics
Volume12
Issue number3
DOIs
StatePublished - 1 Jun 2007

Keywords

  • Gaussian distributions
  • Machine vision
  • Pattern recognition
  • Surveillance

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