抄録

This paper presents an adaptive mixtures-based method for segmenting moving objects in surveillance video with pixel-wise accuracy. The proposed method employs a Gaussian mixture model (GMM) to represent the intensity change of a pixel over time. The GMMconsists of a background component and one or more moving object component(s). The parameters of the GMM are estimated by using an adaptive algorithm that is a non-parametric and data-driven approach. The components in the GMM are subsequently classified into a background and moving objects according to their weights in the GMM. Experimental results demonstrate that the proposed method can successfully and robustly segment the moving objects in surveillance video.

本文言語English
ページ1322-1325
ページ数4
出版ステータスPublished - 2013 1 1
イベント2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013 - Nagoya, Japan
継続期間: 2013 9 142013 9 17

Other

Other2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013
CountryJapan
CityNagoya
Period13/9/1413/9/17

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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