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Intelligent pixels of interest selection with application to facial expression recognition using multilayer perceptron
Abstract : This paper presents an automatic way to discover pixels in a face image that improves the facial expression recognition results. Main contribution of our study is to provide a practical method to improve classification performance of classifiers by selecting best pixels of interest. Our method exhaustively searches for the best and worst feature window position from a set of face images among all possible combinations using MLP. Then, it creates a non-rectangular emotion mask for feature selection in supervised facial expression recognition problem. It eliminates irrelevant data and improves the classification performance using backward feature elimination. Experimental studies on GENKI, JAFFE and FERET databases showed that the proposed system improves the classification results by selecting the best pixels of interest.
Cited literature [36 references]
https://hal.inria.fr/hal-00804171
Contributor : Ioan Marius Bilasco Connect in order to contact the contributor
Submitted on : Saturday, September 29, 2018 - 1:41:57 PM
Last modification on : Thursday, April 30, 2020 - 11:44:24 PM
Long-term archiving on: : Monday, December 31, 2018 - 10:34:13 AM
Contributor : Ioan Marius Bilasco Connect in order to contact the contributor
Submitted on : Saturday, September 29, 2018 - 1:41:57 PM
Last modification on : Thursday, April 30, 2020 - 11:44:24 PM
Long-term archiving on: : Monday, December 31, 2018 - 10:34:13 AM
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Intelligent Pixels of Interest...
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