EigenExpressions for Facial Expression Recognition
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
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Date
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Major features
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1.0
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2007.02.22 |
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We recommend to check the secure connection to PayPal, in order to avoid any fraud. |
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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: 120 EUROS (less than 168 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.
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