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Geometry-Based Facial Expression Recognition Via Large Deformation Diffeomorphic Metric Curve Mapping

IEEE International Conference on Image Processing (ICIP)(2018)CCF C

Sun Yat Sen Univ

Cited 5|Views15
Abstract
We proposed a new geometry-based facial expression recognition (FER) system in the framework of large deformation diffeomorphic metric curve mapping. The geometry of a face was represented by 12 distinct curves, with curve-based facial deformations being used to identify two sets of geometric features in two settings. In each setting, four types of features were extracted and tested. Leave-one-out cross-validation experiments on 327 image sequences yielded accuracies as high as 94%. Furthermore, using a multi-kernel technique to combine features from the two settings has boosted the recognition accuracy to be as high as 95.4%.
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Facial Expression Recognition,Shape,Large Deformation Diffeomorphic Mapping,Curve
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要点】:本研究提出了一种基于大变形微分同胚度量曲线映射的几何面部表情识别系统,实现了高达95.4%的识别准确率。

方法】:通过将面部几何形状表示为12条不同的曲线,并在两种设置中利用曲线基础面部变形来提取两组几何特征。

实验】:采用留一交叉验证方法在327个图像序列上进行实验,使用的是未具体提及的数据集,实验结果达到了94%的准确率,并通过多核技巧结合两种设置中的特征,将识别准确率提高至95.4%。