基于时空面矩的面部表情识别

Yi Ji, Khalid Idrissi
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引用次数: 2

摘要

在本文中,我们提出了一种新的方法来捕捉面部表情引起的动态变形。所提出的方法主要集中在时空平面上,这一领域尚未得到很好的探索。它使用力矩作为特征来描述眼睛和嘴巴等重要组成部分在垂直时间平面上的运动。该系统不仅可以自动识别图像上的表情,还可以自动识别图像序列上的表情。对Cohn-Kanade数据库中95个被试的348条序列进行了实验,对帧的7类识别率为96.1%,对序列的6类识别率为98.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Moments on Spatiotemporal Plane for Facial Expression Recognition
In this paper, we propose a novel approach to capture the dynamic deformation caused by facial expressions. The proposed method is concentrated on the spatiotemporal plane which is not well explored. It uses the moments as features to describe the movements of essential components such as eyes and mouth on vertical time plane. The system we developed can automatically recognize the expression on images as well as on image sequences. The experiments are performed on 348 sequences from 95 subjects in Cohn-Kanade database and obtained good results as high as 96.1% in 7-class recognition for frames and 98.5% in 6-class for sequences.
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