DocumentCode :
2821860
Title :
An Adaptive Fuzzy Neural Network for Extracting Scene Image Parameters
Author :
Gong, Wei ; Feng, Donghui ; Feng, Xin
Author_Institution :
Sch. of Comput., Commun. Univ. of China, Beijing, China
Volume :
2
fYear :
2009
fDate :
24-26 April 2009
Firstpage :
350
Lastpage :
353
Abstract :
As the most important objective parameters, reverberation time and clarity play significant roles in acoustic field characteristics evaluation of the hall. We can get it by measuring an actual room. In this paper, a new method is proposed based on adaptive fuzzy neural network to extract the reverberation time and clarity from a scene image. Finally the validity of the network is proved through the experiment results of network training on the test data. It provides a brand-new idea for virtual reality technique and sound quality evaluation of virtual environment with using this method.
Keywords :
acoustic signal processing; architectural acoustics; feature extraction; fuzzy neural nets; image texture; learning (artificial intelligence); reverberation; virtual reality; acoustic field characteristics evaluation; adaptive fuzzy neural network training; image texture; reverberation time; scene image parameter extraction; sound quality evaluation; virtual reality; Acoustic measurements; Adaptive systems; Computer networks; Data mining; Fuzzy neural networks; Input variables; Layout; Psychoacoustic models; Reverberation; Virtual reality;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Sciences and Optimization, 2009. CSO 2009. International Joint Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-0-7695-3605-7
Type :
conf
DOI :
10.1109/CSO.2009.60
Filename :
5193968
Link To Document :
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