Geometrical Approaches for Facial Expression Recognition Using Support Vector Machines

机译：支持向量机用于面部表情识别的几何方法

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This article presents two facial geometric-based approaches for facial expression recognition using support vector machines. The first method performed an experimental research to identify the relevant geometric features for human point of view and achieved 85% of recognition rate. The second experiment employed the Correlation Feature Selection and achieved 96.11% of recognition rate. All experiments were carried out with Cohn-Kanade database and the results obtained are compatible with the state-of-the-art in this in this research area.

机译：本文介绍了使用支持向量机进行面部表情识别的两种基于面部几何的方法。第一种方法进行了实验研究，以识别人眼相关的几何特征，并达到了85％的识别率。第二个实验采用了“相关特征选择”，达到了96.11％的识别率。所有实验均使用Cohn-Kanade数据库进行，所得结果与该研究领域的最新技术相吻合。

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《SIBGRAPI Conference on Graphics, Patterns and Images》|2016年|347-354|共8页
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Jovan de Andrade Fernandes; Leonardo Nogueira Matos; Maria Géssica dos Santos Aragão;
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Feature extraction; Face recognition; Shape; Face; Support vector machines; Databases; Eyebrows;

机译：特征提取人脸识别形状人脸支持向量机数据库眉毛;

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1. Features classification using geometrical deformation feature vector of support vector machine and active appearance algorithm for automatic facial expression recognition [J] . Rajesh A. Patil, Vineet Sahula, A. S. Mandal Machine Vision and Applications . 2014,第3期

机译：利用支持向量机的几何变形特征向量和主动出现算法进行面部表情自动识别的特征分类
2. Recognition of facial expressions based on salient geometric features and support vector machines [J] . Ghimire Deepak, Lee Joonwhoan, Li Ze-Nian, Multimedia Tools and Applications . 2017,第6期

机译：基于显着几何特征和支持向量机的面部表情识别
3. Geometric Feature-Based Facial Expression Recognition in Image Sequences Using Multi-Class AdaBoost and Support Vector Machines [J] . Deepak Ghimire, Joonwhoan Lee Sensors . 2013,第6期

机译：使用多类AdaBoost和支持向量机的图像序列中基于几何特征的面部表情识别
4. Geometrical Approaches for Facial Expression Recognition Using Support Vector Machines [C] . Jovan de Andrade Fernandes, Leonardo Nogueira Matos, Maria Géssica dos Santos Arag?o SIBGRAPI Conference on Graphics, Patterns and Images . 2016

机译：使用支持向量机面部表情识别的几何方法
5. Geometric Approach to Support Vector Machines Learning for Large Datasets [D] . Strack, Robert 2013

机译：支持矢量机学习大数据集的几何方法
6. Geometric Feature-Based Facial Expression Recognition in Image Sequences Using Multi-Class AdaBoost and Support Vector Machines [O] . Deepak Ghimire, Joonwhoan Lee 2013

机译：使用多类AdaBoost和支持向量机的图像序列中基于几何特征的面部表情识别
7. Recognition of facial expressions based on salient geometric features and support vector machines [O] . Deepak Ghimire, Joonwhoan Lee, Ze-Nian Li, 2016

机译：基于突出几何特征和支持向量机的面部表达识别

Geometrical Approaches for Facial Expression Recognition Using Support Vector Machines

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