Compact local Gabor directional number pattern for facial expression recognition

Authors

ZHENGYAN ZHANG
GUANMING LU
JINGJIE YAN
HAIBO LI
NING SUN
XIA LI

DOI

10.3906/elk-1711-2

Abstract

This paper explores a novel method to represent face images for facial expression recognition; it is named compact local Gabor directional number pattern (CLGDNP). By convolving the face images with Gabor filters, we encode the magnitude and phase response images in each scale, and calculate the histograms in several nonoverlapping regions of each encoded image. Finally, we obtain two spatial histogram sequences by the aid of the mean pooling technology and concatenate them to form the facial descriptor. Moreover, for evaluating the performance of the proposed method, we employ a support vector machine to conduct some extensive classification experiments on the Radboud faces database, the extended Cohn-Kanade database, and the Japanese Female Facial Expression database. The experimental results demonstrate that the proposed CLGDNP method achieves better performance in classification.

Keywords

Facial expression recognition, compact local Gabor directional number pattern, Gabor filters, feature, support vector machine

First Page

1236

Last Page

1248

Recommended Citation

ZHANG, ZHENGYAN; LU, GUANMING; YAN, JINGJIE; LI, HAIBO; SUN, NING; and LI, XIA (2018) "Compact local Gabor directional number pattern for facial expression recognition," Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 26: No. 3, Article 10. https://doi.org/10.3906/elk-1711-2
Available at: https://journals.tubitak.gov.tr/elektrik/vol26/iss3/10