A method of facial expression recognition based on Gabor and NMF

The technology of facial expression recognition is a challenging problem in the field of intelligent human-computer interaction. An algorithm based on the Gabor wavelet transformation and non-negative matrix factorization (G-NMF) is presented. The main process includes image preprocessing, feature e...

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Bibliographic Details
Published in:Pattern recognition and image analysis 2016, Vol.26 (1), p.119-124
Main Authors: Zhou, Jun, Zhang, Sue, Mei, Hongyan, Wang, Dawei
Format: Article
Language:English
Subjects:
Analysis
Applied Problems
Classification
Computer Science
Face
Face recognition
Factorization
Feature extraction
Image Processing and Computer Vision
Methods
Pattern Recognition
Preprocessing
Principal components analysis
Studies
Transformations
Wavelet
Wavelet transforms
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Summary:The technology of facial expression recognition is a challenging problem in the field of intelligent human-computer interaction. An algorithm based on the Gabor wavelet transformation and non-negative matrix factorization (G-NMF) is presented. The main process includes image preprocessing, feature extraction and classification. At first, the face region containing emotional information is obtained and normalized. Then, expressional features are extracted by Gabor wavelet transformation and the high-dimensional data are reduced by non-negative matrix factorization (NMF). Finally, two-layer classifier (TLC) is designed for expression recognition. Experiments are done on JAFFE facial expressions database. The results show that the method proposed has a better performance.
ISSN:1054-6618
1555-6212
DOI:10.1134/S1054661815040070