TITLE:
Facial Expression Recognition Based on Local Fourier Coefficients and Facial Fourier Descriptors
AUTHORS:
Gibran Benitez-Garcia, Tomoaki Nakamura, Masahide Kaneko
KEYWORDS:
Facial Expression Recognition, Fourier Coefficients, Fourier Descriptors, Facial Region Segmentation, Partial Occlusion
JOURNAL NAME:
Journal of Signal and Information Processing,
Vol.8 No.3,
July
31,
2017
ABSTRACT: The recent boom of mass media communication (such as social media and mobiles) has boosted more applications of automatic facial expression recognition (FER). Thus, human facial expressions have to be encoded and recognized through digital devices. However, this process has to be done under recurrent problems of image illumination changes and partial occlusions. Therefore, in this paper, we propose a fully automated FER system based on Local Fourier Coefficients and Facial Fourier Descriptors. The combined power of appearance and geometric features is used for describing the specific facial regions of eyes-eyebrows, nose and mouth. All based on the attributes of the Fourier Transform and Support Vector Machines. Hence, our proposal overcomes FER problems such as illumination changes, partial occlusion, image rotation, redundancy and dimensionality reduction. Several tests were performed in order to demonstrate the efficiency of our proposal, which were evaluated using three standard databases: CK+, MUG and TFEID. In addition, evaluation results showed that the average recognition rate of each database reaches higher performance than most of the state-of-the-art techniques surveyed in this paper.