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A new manifold representation for visual speech recognition

Yu, Dahai and Ghita, Ovidiu and Sutherland, Alistair and Whelan, Paul F. (2007) A new manifold representation for visual speech recognition. In: IMVIP 2007 - 11th International Machine Vision and Image Processing Conference, 5-7 September 2007, Maynooth, Ireland.

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Abstract

In this paper, we propose a new manifold representation for visual speech recognition. The developed system consists of three main steps: a. Lip extraction from input video data. b. Generate the Expectation-Maximization PCA (EMPCA) manifolds for the entire image sequence and perform manifold interpolation and re-sampling. c. Classify the manifolds using a HMM classifier to identify the words described by the lips motions in the input video sequence.

Item Type:	Conference or Workshop Item (Paper)
Event Type:	Conference
Refereed:	Yes
Subjects:	Computer Science > Digital video Computer Science > Information retrieval
DCU Faculties and Centres:	Research Initiatives and Centres > Centre for Digital Video Processing (CDVP) DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering Research Initiatives and Centres > Research Institute for Networks and Communications Engineering (RINCE) DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Publisher:	Institute of Electrical and Electronics Engineers
Official URL:	http://dx.doi.org/10.1109/IMVIP.2007.4
Copyright Information:	Copyright © 2007 IEEE. Reprinted from IMVIP 2007 - Proceedings of the 11th International Machine Vision and Image Processing Conference. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Dublin City University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
ID Code:	219
Deposited On:	05 Mar 2008 by DORAS Administrator. Last Modified 03 Jul 2009 11:59

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