Facial Expression Recognition based on Gabor Wavelet Transform and Histogram of Oriented Gradients

被引：0

作者：

Xu, Xiaoming ^{[1
]}

Quan, Changqin ^{[2
]}

Ren, Fuji ^{[3
]}

机构：

[1] Hefei Univ Technol, Sch Comp & Informat, Hefei 230009, Peoples R China

[2] Kobe Univ, Grad Sch Syst Informat, Kobe, Hyogo 6578501, Japan

[3] Univ Tokushima, Tokushima 7708501, Japan

来源：

2015 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION | 2015年

关键词：

Affective Computing; Histogram of Oriented Gradients; Gabor Wavelet Transform; Facial Expression Recognition; INTENSITY;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In order to get more effective expression features, this paper proposes an approach based on Gabor feature and Histogram of Oriented Gradients (HOG). Gabor Wavelet filter is first used as preprocessing stage for feature extraction. Handing the characteristics with a large number of dimensions, binary encoding (BC) is applied for dimensionality reduction. Dimensionality of the feature vector is reduced by using HOG algorithm. Experiments were performed on Cohn-Kanade facial expression database and the support vector machine classifier is used for expression classification. We obtained experimental results with an average recognition rate of 92.5%, which reveals that the proposed method is superior to other Gabor Wavelet transform based approaches under the same experimental environment.

引用

页码：2117 / 2122

页数：6

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