基于差分纹理的人脸表情识别

被引：3

作者：

夏海英 ^{[1
,2
,3
]}

徐鲁辉 ^{[1
]}

机构：

[1] 广西师范大学电子工程学院

[2] 广西师范大学药用资源化学与药物分子工程教育部重点实验室

[3] 桂林电子科技大学广西自动检测技术与仪器重点实验室

来源：

计算机应用研究 | 2015年 / 32卷 / 11期

关键词：

面部表情; Delaunay三角剖分; 差分纹理特征; 主动形状模型;

D O I：

暂无

中图分类号：

TP391.41 [];

学科分类号：

080203 ;

摘要：

考虑到自动人脸表情识别背景复杂性问题,提出了一个新的表情识别方法——基于差分纹理的人脸表情识别,该方法在一定程度上能够有效地屏蔽掉个体人脸之间的差异,同时保留住人脸表情信息。首先选定一个标准人脸参考模型,该模型合理分布面部55个基准点,这些基准点主要分布于眼睛、鼻子、嘴和包含表情丰富的外部轮廓上;然后利用Delaunay三角剖分获取这些基准点的相对位置信息。对于人脸表情图像,首先利用主动形状模型(ASM)跟踪定位这55个基准点,然后利用三角剖分获得的相对位置信息,以及应用纹理映射技术将表情图像映射到标准人脸参考模型中,这样中性表情图像(不含表情信息的人脸)和非中性表情(六种基本表情)图像均被映射到同一大小的框架内,最后将它们的差值图像作为表情特征,称为DT(differential texture,差分纹理)特征。最后分别将JAFFE人脸表情库和CK人脸表情库中的部分样本组成混合数据并进行实验,结果表明提出的方法对六种基本表情具有较好的识别率,并且该方法优于传统的Gabor特征和LBP特征方法,并能扩展到动态图像中的表情识别中去。

引用

页码：3504 / 3507

页数：4

共 14 条

[1]

AAM based continuous facial expression recognition for face image sequences. HOMMEL S,HANDMANN U. Proceedings of the 12th International Symposium on Computational Intelligence and Informatics . 2011

[2]

Texture Classification by Using Advanced Local Binary Patterns and Spatial Distribution of Dominant Patterns. Shu Liao,Chung AC S. Proc of the IEEE International Conference on Acoustics,Speech and Signal Processing . 2007

[3]

Facial expression recognition based on fusion of Gabor and LBP features. ZHAO Quan-you,PAN Bao-chang,PAN Jian-jia,et al. ICWAPR.6th International Conference on Wavelet Analysis and Pattern Recognition . 2008

[4]

Locating facial features with an extended active shape model. Stephen Milborrow,Fred Nicolls. Proceedings of The 10th European Conference on Computer Vision . 2008

[5]

Fuzzy local binary patterns:a comparison between Min-Max and Dot-Sum operators in the application of facial expression recognition. Mohammadi M R,Fatemizadeh E. Proc of the 8th Iranian Conference on Machine Vision and Image Processing . 2013

[6]

Facial Expression Recognition Based on Gabor Wavelet Phase Features. SHI Dongcheng,CAI Fang,DU Guangyi. The 7th International Conference of Image and Graphics . 2013

[7]

Automatic analysis of facial expressions: the state of the art. Pantic M,Rothkrantz L J M. IEEE Transactions on Pattern Analysis and Machine Intelligence . 2000

[8]

Dynamic texture recognition using local binary patterns with an application to facial expressions. G Zhao,M Pietika?inen. IEEE Transactions on Pattern Analysis and Machine Intelligence . 2007

[9]

Graph-Preserving Sparse Nonnegative Matrix Factorization With Application to Facial Expression Recognition. Ruicong Zhi,Markus Flierl,Qiuqi Ruan. IEEE Transactions on Systems Man and Cybernetics . 2011

[10]

Automatic facial expression analysis: a survey[J] . B. Fasel,Juergen Luettin. &nbspPattern Recognition . 2002 (1)

← 1 2 →