Title :
The background modeling for the video sequences using Radial Basis Function neural network
Author :
Rohanifar, Marjan ; Amiri, Ali
Author_Institution :
Comput. Eng., Islamic Azad Univ., Zanjan, Iran
fDate :
Nov. 29 2011-Dec. 1 2011
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 RBF1 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.
Keywords :
image sequences; radial basis function networks; RBF neural network; Wallflower data set; background modeling; background subtraction system; radial basis function neural network; two-state machine; video sequences; Adaptation models; Biological neural networks; Estimation; Gaussian distribution; Radial basis function networks; Real-time systems; Surveillance; Background Estimation - RBF neural Networks - finite state machine;
Conference_Titel :
Computer Sciences and Convergence Information Technology (ICCIT), 2011 6th International Conference on
Conference_Location :
Seogwipo
Print_ISBN :
978-1-4577-0472-7