JOURNAL ARTICLE

A moving objects detection algorithm using iterative division and Gaussian mixture model

Abstract

In the fields of intelligent video surveillance, video analysis and computer vision, moving objects detection is one of the fundamental tasks. In this paper, we present an algorithm for moving objects detection based on Gaussian mixture model and iterative division, which can be used for real time processing. We use iterative division algorithm to filter illumination variation and local variations. Then, GMM is used to update background and get pixel level precision. Experimental results show that our method, by the combination of iterative division and GMM, is able to overcome deficiency of tradition method and gain good detection results.

Keywords:
Division (mathematics) Computer science Iterative method Mixture model Algorithm Artificial intelligence Computer vision Gaussian Pixel Filter (signal processing) Division algorithm Pattern recognition (psychology) Mathematics

Metrics

4
Cited By
0.96
FWCI (Field Weighted Citation Impact)
15
Refs
0.76
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Remote Sensing and Land Use
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science
Advanced Measurement and Detection Methods
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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