Facial expression recognition using shape and texture information

Kotsia, Irene and Pitas, Ioannis (2006) Facial expression recognition using shape and texture information. In: IFIP TC12 and WG12.5: Conference and Symposium on Artificial Intelligence, 21-24 August 2006, Santiago, Chile.

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Official URL: http://www.ifiptc12.org/

Abstract

A novel method based on shape and texture information is proposed in this paper for facial expression recognition from video sequences. The Discriminant Non-negative Matrix Factorization (DNMF) algorithm is applied at the image corresponding to the greatest intensity of the facial expression (last frame of the video sequence), extracting that way the texture information. A Support Vector Machines (SVMs) system is used for the classification of the shape information derived from tracking the Candide grid over the video sequence. The shape information consists of the differences of the node coordinates between the first (neutral) and last (fully expressed facial expression) video frame. Subsequently, fusion of texture and shape information obtained is performed using Radial Basis Function (RBF) Neural Networks (NNs). The accuracy achieved is equal to 98.2 % when recognizing the six basic facial expressions.

Item Type: Conference or Workshop Item (Paper)
Additional Information: A conference as part of IFIP World Computer Congress (WCC2006).
Research Areas: A. > School of Science and Technology > Computer Science
A. > School of Science and Technology > Computer Science > Intelligent Environments group
Item ID: 9679
Useful Links:
Depositing User: Devika Mohan
Date Deposited: 28 Dec 2012 06:39
Last Modified: 13 Oct 2016 14:25
URI: http://eprints.mdx.ac.uk/id/eprint/9679

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