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Facial grid transformation: A novel face registration approach for improving facial action unit recognition

机译：面部网格转换：一种新颖的面部注册方法，可改善面部动作单元的识别能力

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Face registration is a major and critical step for face analysis. Existing facial activity recognition systems often employ coarse face alignment based on a few fiducial points such as eyes and extract features from equal-sized grid. Such extracted features are susceptible to variations in face pose, facial deformation, and person-specific geometry. In this work, we propose a novel face registration method named facial grid transformation to improve feature extraction for recognizing facial Action Units (AUs). Based on the transformed grid, novel grid edge features are developed to capture local facial motions related to AUs. Extensive experiments on two well-known AU-coded databases have demonstrated that the proposed method yields significant improvements over the methods based on equal-sized grid on both posed and more importantly, spontaneous facial displays. Furthermore, the proposed method also outperforms the state-of-the-art methods using either coarse alignment or mesh-based face registration.
机译：人脸登记是人脸分析的重要步骤。现有的面部活动识别系统通常基于诸如眼睛之类的一些基准点来采用粗糙的面部对准，并且从相等大小的网格中提取特征。这样提取的特征易于出现面部姿势，面部变形和特定于人的几何形状的变化。在这项工作中，我们提出了一种新的人脸注册方法，称为人脸网格变换，以改善特征提取以识别人脸动作单元（AUs）。基于转换后的网格，开发了新颖的网格边缘特征以捕获与AU相关的局部面部运动。在两个著名的AU编码数据库上进行的大量实验表明，与基于等尺寸网格的摆姿势（更重要的是自发的面部显示器）的方法相比，该方法产生了显着的改进。此外，所提出的方法还优于使用粗对准或基于网格的人脸配准的最新技术。

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