Background Modeling using Mixture of Gaussians for Foreground Detection - A Survey - Archive ouverte HAL Access content directly
Journal Articles Recent Patents on Computer Science Year : 2008

Background Modeling using Mixture of Gaussians for Foreground Detection - A Survey

Abstract

Mixture of Gaussians is a widely used approach for background modeling to detect moving objects from static cameras. Numerous improvements of the original method developed by Stauffer and Grimson [1] have been proposed over the recent years and the purpose of this paper is to provide a survey and an original classification of these improvements. We also discuss relevant issues to reduce the computation time. Firstly, the original MOG are reminded and discussed following the challenges met in video sequences. Then, we categorize the different improvements found in the literature. We have classified them in term of strategies used to improve the original MOG and we have discussed them in term of the critical situations they claim to handle. After analyzing the strategies and identifying their limitations, we conclude with several promising directions for future research.
Fichier principal
Vignette du fichier
RPCS_2008.pdf (373.16 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00338206 , version 1 (12-11-2008)

Identifiers

  • HAL Id : hal-00338206 , version 1

Cite

Thierry Bouwmans, Fida El Baf, Bertrand Vachon. Background Modeling using Mixture of Gaussians for Foreground Detection - A Survey. Recent Patents on Computer Science, 2008, 1 (3), pp.219-237. ⟨hal-00338206⟩

Collections

MIA UNIV-ROCHELLE
1760 View
24858 Download

Share

Gmail Facebook X LinkedIn More