Performance analysis of frequency domain based feature extraction techniques for facial expression recognition
Facial Expression Recognition is a vital topic for research in current scenario which has many applications as machine based HR interviews and human machine interaction. Facial Expression recognition is applied for identification of person using face of a person. Researchers have proposed many research techniques for facial expression recognition but still accuracy, illumination and occlusion are the research issues which have to improve. Key Research issue of facial expression is improving the accuracy of system which is measured in term of recognition rate. Feature extraction is the main stage on which accuracy depends for facial expression recognition. In this paper we have analyzed different feature extraction technique in frequency domain as Discrete Wavelet Transform, Discrete Cosine Transform feature extraction technique, Gabor filter and different feature reduction technique developed so far and future aspects.
2017 7th International Conference on Cloud Computing, Data Science Engineering Confluence