基于对称双线性模型的光照鲁棒性人脸表情识别

刘帅师; 田彦涛; 王新竹

doi:10.3724/SP.J.1004.2012.01933

基于对称双线性模型的光照鲁棒性人脸表情识别

doi: 10.3724/SP.J.1004.2012.01933

1.
吉林大学控制科学与工程系长春 130025;
2.
长春工业大学自动化系长春 130012

详细信息

通讯作者:
田彦涛

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- 被引次数: 0
出版历程
- 收稿日期: 2012-01-19
- 修回日期: 2012-06-15
- 刊出日期: 2012-12-20

Illumination-robust Facial Expression Recognition Based on Symmetric Bilinear Model

1.
Department of Control Science and Engineering, Jilin University, Changchun 130025;
2.
Department of Automation, Changchun University of Technology, Changchun 130012

摘要

摘要: 针对传统的光照预处理方法降低原始图像质量、丢失部分有效辨识信息的缺点,提出一种新颖的应用对称双线性模型来对人脸表情图像进行光照预处理的光照鲁棒性人脸表情识别方法.首先通过对称双线性模型将训练集图像分解为相互独立的光照因子和表情因子,并提取其光照因子.接下来提取含有未知光照的测试集表情图像的表情因子,并将其转换到训练集的若干个已知光照上,这样处理能够将任意光照的测试图像转换到相同的光照平台上,令所有测试图像的特征具有归一化特性.实验结果表明, 本文所提光照预处理方法在识别性能上优于传统的光照预处理方法,应用在光照处理后的JAFFE表情库上识别率达到92.37%, 表明其适用于光照鲁棒性人脸表情识别.
- 对称双线性模型 /
- 光照预处理 /
- 光照鲁棒性 /
- 表情识别
Abstract: This paper proposes a novel illumination-robust facial expression recognition method using symmetric bilinear model to overcome the disadvantage of traditional illumination preprocessing methods that can degrade the quality of input image and worsen recognition performance. Firstly, the illumination factors are separated from the training database. Secondly, the expression factor is separated from testing image with arbitrary illumination. Thirdly, the testing image is transformed into a number of expression images exhibiting different illuminations of training database. Experimental results show that the proposed method is better than the traditional illumination preprocessing methods in recognition performance. The best recognition rate of 92.37% is achieved in JAFFE database with illumination transformation, indicating this method is suitable for illumination-robust facial expression recognition.
- Symmetric bilinear model /
- illumination preprocessing /
- illumination-robust /
- expression recognition

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参考文献(1)

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