A Study on Facial Expression Recognition

Abstract

This study focuses on the issue of automatic Facial Expression Recognition (FER) on little databases of 2D faces. Convolutional Neural Networks (CNN) is a relatively new classification technique, which reaches the state of the art on big databases; however, the use of CNN with a scarce number of samples is still an open and interesting challenge. Following the classical machine learning approach, we considered different combination of appearance based projection methods, feature extraction techniques and classifiers, and we compared their performances with special designed CNN. Experimental results underline the drawback of CNN with scares labeled data.

Keywords

• Little databases,facial expression,sparse representation based classifier,convolutional neural net

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