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We propose an algorithm for facial expression recognition
which can classify the given image into one of the seven
basic facial expression categories (happiness, sadness, fear, surprise, anger, disgust and neutral).
PCA is used for dimensionality reduction in input data while retaining those characteristics of the
data set that contribute most to its variance, by keeping lower-order principal components and ignoring
higher-order ones. Such low-order components contain the "most important" aspects of the data.
The extracted feature vectors in the reduced space are used to train the supervised Neural Network
classifier. This approach results extremely powerful because it does not require the
detection of any reference point or node grid. The proposed method is fast and can be
used for real-time applications.
This code has been tested using the JAFFE Database, available at http://www.kasrl.org/jaffe.html.
Using 150 images randomly selected for training and 63 images for testing, without any overlapping,
we obtain an excellent recognition rate greater than 83%. The semantic data ratings for this
database are available at http://www.kasrl.org/jaffe_info.txt.
Index Terms: Matlab, source, code, facial, expression, recognition, JAFFE, neural networks, PCA, network, expressions, face, principal component analysis.
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Figure 1. Facial expression extracted from JAFFE Database |
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A simple and effective source code for Facial Expression Recognition. |
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Demo code (protected
P-files) available for performance evaluation. Matlab Image Processing Toolbox and Matlab Neural Network Toolbox are required.
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Release |
Date |
Major features |
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1.0 |
2007.02.22 |
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We recommend to check the secure connection to PayPal, in order to avoid any fraud. This donation has to be considered an encouragement to improve the code itself. |
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Facial Expression Recognition. Click here for
your donation. In order to obtain the source code you
have to pay a little sum of money: 30 EUROS (less
than 42 U.S. Dollars). |
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Once you have done this, please email us luigi.rosa@tiscali.it As soon as possible (in a few days) you will receive our new release of Facial Expression Recognition System. Alternatively, you can bestow using our banking coordinates:
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The authors have no relationship or partnership
with The Mathworks. All the code provided is written in Matlab
language (M-files and/or M-functions), with no dll or other
protected parts of code (P-files or executables). The code was
developed with Matlab 14 SP1. Matlab Image Processing Toolbox and Matlab Neural Network Toolbox are required.
The code provided has to be considered "as is" and it is without any kind of warranty. The
authors deny any kind of warranty concerning the code as well
as any kind of responsibility for problems and damages which may
be caused by the use of the code itself including all parts of
the source code.
