Share Email Print

Proceedings Paper

Facial micro-expression recognition based on local region of the key frame
Author(s): Wenjun Zhong; Xinhe Yu; Ling Shi; Zhihua Xie
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Traditional studies on micro-expression feature extraction primarily focused on global face from all frames. To improve the efficiency of feature extraction, this paper proposes a new framework based on the local region and the key frame to represent facial micro-expressions. Firstly, the face feature point detection technique is used to acquire the coordinates of the 68 key points, and the region of interest is divided by those key point coordinates and the action unit. Secondly, in order to remove redundant information in the micro-expression video sequence, structural similarity index (SSIM) is used to select key frames for each local region of interest. Finally, the dual-cross patterns (DCP) are extracted for the local regions of interest and are concatenated into a feature vector for the final classification. The experimental results show that compared with the traditional micro-expression method, the proposed method has higher recognition rate and achieves better time computation performance.

Paper Details

Date Published: 14 February 2020
PDF: 7 pages
Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 114301L (14 February 2020); doi: 10.1117/12.2539437
Show Author Affiliations
Wenjun Zhong, Jiangxi Science and Technology Normal Univ. (China)
Xinhe Yu, Jiangxi Science and Technology Normal Univ. (China)
Ling Shi, Jiangxi Science and Technology Normal Univ. (China)
Zhihua Xie, Jiangxi Science and Technology Normal Univ. (China)

Published in SPIE Proceedings Vol. 11430:
MIPPR 2019: Pattern Recognition and Computer Vision
Nong Sang; Jayaram K. Udupa; Yuehuan Wang; Zhenbing Liu, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?