NDLI: The background modeling for the video sequences using Radial Basis Function neural network

Content Provider	IEEE Xplore Digital Library
Author	Rohanifar, M. Amiri, A.
Copyright Year	2011
Description	Author affiliation: Comput. Eng. Group, Univ. of Zanjan, Zanjan, Iran (Amiri, A.) \|\| Comput. Eng., Islamic Azad Univ., Zanjan, Iran (Rohanifar, M.)
Abstract	This paper an adapted background subtraction system based on Radial Basis Function neural network is given. In the suggested system for each background pixel a two-state machine is considered in which the $RBF^{1}$ neural network is used for crossing between different states of the machine. In suggested system is flexible to light changes and very few movements of background object and the presence of new object in the background and other challenges mentioned in the field of estimate the background. The test are down on image group of Wallflower data set, the obtained result confirm the efficiency of the suggested solution.
Sponsorship	IEEE
Starting Page	371
Ending Page	374
File Size	386867
Page Count	4
File Format	PDF
ISBN	9781457704727
e-ISBN	9788988678558
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-29
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	AICIT
Subject Keyword	Adaptation models Background Estimation - RBF neural Networks - finite state machine Surveillance Estimation Radial basis function networks Gaussian distribution Real-time systems Biological neural networks
Content Type	Text
Resource Type	Article

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The background modeling for the video sequences using Radial Basis Function neural network