Enhanced audio-visual recognition system over internet protocol

Yee Wan Wong; Kah Phooi Seng; Li-Minn Ang

doi:10.1007/978-90-481-3517-2_11

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Enhanced audio-visual recognition system over internet protocol

Book chapter

Peer reviewed

Enhanced audio-visual recognition system over internet protocol

Yee Wan Wong, Kah Phooi Seng and Li-Minn Ang

Intelligent Automation and Computer Engineering, pp.137-149

Lecture Notes in Electrical Engineering (LNEE), 52, Springer Netherlands

2010

DOI: https://doi.org/10.1007/978-90-481-3517-2_11

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Abstract

Audio-visual recognition system

Illumination variation

Internet protocol

Multiband feature fusion

Neural network

In this chapter, we extend the research work in Wong and enhance the audio-visual recognition system over internet protocol. The multiband feature fusion method is presented to solve the illumination problem. Then a radial basis function neural network with a new orthogonal least square algorithm is proposed to improve the generalization of the radial basis function neural network with conventional orthogonal least square algorithm. Result shows that the proposed neural network achieves higher recognition accuracy with lesser number of neurons as compared to the neural network with conventional orthogonal least square algorithm. With this neural network, the recognition accuracy of the audio-visual recognition system is improved as compared to the audio-visual recognition system in Wong. Then the audio-visual recognition system over internet protocol is developed where the multiband feature fusion and the proposed neural network are implemented.

Details

Title: Enhanced audio-visual recognition system over internet protocol
Authors: Yee Wan Wong (Author) - University of Nottingham Malaysia Campus
Kah Phooi Seng (Author) - University of Nottingham Malaysia Campus
Li-Minn Ang (Author) - University of Nottingham Malaysia Campus
Contributors: Xu Huang (Editor) - University of Canberra
Sio-Iong Ao (Editor) - International Association of Engineers
Oscar Castillo (Editor) - Instituto Tecnológico de Tijuana
Publication details: Intelligent Automation and Computer Engineering, pp.137-149
Series: Lecture Notes in Electrical Engineering (LNEE); 52
Publisher: Springer Netherlands
Date published: 2010
DOI: 10.1007/978-90-481-3517-2_11; 10.1007/978-90-481-3517-2
ISSN: 1876-1100; 1876-1119
ISBN: 9789048135172
Organisation Unit: University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Engage Research Lab
Language: English
Record Identifier: 99513891102621
Output Type: Book chapter

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