Facial expression representation and classification using 2DPCA

This paper's purpose is to compare the performance between the two feature extraction methods PCA and 2DPCA by applying them to feature extraction stage in the facial expression classification model. To test and evaluate their performance, we performed experiments on two face image databases: J...

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Bibliographic Details
Main Authors: Le Hoang Thai, Do Thi Thanh Ha
Format: Conference Proceeding
Language:English
Subjects:
Covariance matrix
Face
Feature extraction
Principal component analysis
Training
Vectors
Online Access:Request full text
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Summary:This paper's purpose is to compare the performance between the two feature extraction methods PCA and 2DPCA by applying them to feature extraction stage in the facial expression classification model. To test and evaluate their performance, we performed experiments on two face image databases: JAFFE and YALE. The experimental results also indicated that the performance and speed of 2DPCA are better than PCA in feature extraction capabilities.
DOI:10.1109/ICCAIS.2012.6466628