Facial expression recognition using sparse coding

In this paper a sparse coding approach is proposed. Due to the similarity of the frequency and orientation representations of Gabor filters and those of the human visual system, we have used Gabor filters in the step of creating the dictionary. It has been shown that not all Gabor filters in a typical Gabor bank is necessary and efficient in facial expression recognition. Also we proposed a voting system in the test phase of algorithm to find the best matching expression. The well known JAFFE database has been used to evaluate the proposed method and our experimental results show encouraging results within the mentioned database.