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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Siti Suhana Jamaian
Universiti Tun Hussein Onn Malaysia
Computer Science & IT Engineering

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Background subtraction challenges in motion detection using Gaussian mixture model: a survey Nor Afiqah Mohd Aris; Siti Suhana Jamaian
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 3: September 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i3.pp1007-1018

Abstract

Motion detection is becoming prominent for computer vision applications. The background subtraction method that uses the Gaussian mixture model (GMM) is utilized frequently in camera or video settings. However, there is still more work that needs to be done to develop a reliable, accurate and high-performing technique due to various challenges. The degree of difficulty for this challenge is primarily determined by how the object to be detected is defined. It could be influenced by the changes in the object posture or deformations. In this context, we describe and bring together the most significant challenges faced by the background subtraction techniques based on GMM for dealing with a crucial background situation. Therefore, the findings of this study can be used to identify the most appropriate GMM version based on the crucial background situation.
Co-Authors Nor Afiqah Mohd Aris