DMCA
Facial expression recognition using shape and texture information
| Venue: | IFIP International Federation for Information Processing, 2006, Volume 217, Artificial Intelligence in Theory and Practice |
| Citations: | 2 - 0 self |
BibTeX
@INPROCEEDINGS{Kotsia_facialexpression,
author = {I Kotsia and I Pitas},
title = {Facial expression recognition using shape and texture information},
booktitle = {IFIP International Federation for Information Processing, 2006, Volume 217, Artificial Intelligence in Theory and Practice},
year = {},
pages = {365--374}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
Summary. 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.
