A Novel Approach to Detect Foreground in Video Sequences Based on Mixture of Gaussians |
Author(s): |
| Navneet S. Ghedia , Sanjaybhai Rajguru College of Engineering,Rajkot; Prof. Dr. C.H. Vithalani, Government Engineering College,Rajkot; Prof. Dr. Kiran Parmar, Retired Professor- GEC gandhinagar |
Keywords: |
| video surveillance and monitoring, adaptive Gaussian mixture model, background model, Gaussian mixture density, foreground detection |
Abstract |
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Our aim is to develop a robust visual monitoring system that passively detects moving objects in a specified space and identify the activities of those objects. In the paper, we focus on foreground detection. Mixture of Gaussian is a very well know and friendly approach for background modelling to detect moving objects. Our method improves Gaussian mixture model by continuously updating the mixture parameters. It gives faster update and a smoother object mask. The Gaussian mixture model approach consists of different Gaussian distributions, mean, standard deviation, weight. So, focus is to develop a robust visual monitoring system which can work successfully against illumination variations, clutter background, slow moving objects, sawing trees and objects being introduced or removed from the frame. |
Other Details |
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Paper ID: IJSRDV3I60636 Published in: Volume : 3, Issue : 6 Publication Date: 01/09/2015 Page(s): 1220-1224 |
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