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Expression robust three-dimensional face recognition based on gaussian filter and dual-tree complex wavelet transform

机译:基于高斯滤波器和双树复小波变换的表情鲁棒三维人脸识别

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摘要

In this paper, a fully automatic framework is proposed for 3D face recognition and its superiority performance is justified by the FRGC v2 data. For 3D data preprocessing, a new face smoothing method is proposed. Meanwhile, 3D facial representation, which is extracted by the Dual-tree Complex Wavelet Transform (DT-CWT), is introduced to reflect the facial geometry properties. Low redundancy makes it more effective and efficient to describe the discriminant feature in 2.5D range data. In this paper, DT-CWT is used into 2.5D range data in conjunction with the Linear Discriminant Analysis (LDA) to form a rejection classifier, which can quickly eliminate a large number of candidate gallery faces. The remaining faces are then verified using sparse representation based classification. Our method achieves the verification rate of 98.66% on All vs. All experiment at an FAR of 0.1%.
机译:本文提出了一种用于3D人脸识别的全自动框架,并通过FRGC v2数据证明了其优越的性能。对于3D数据预处理,提出了一种新的人脸平滑方法。同时,引入了通过双树复数小波变换(DT-CWT)提取的3D面部表示,以反映面部几何特性。低冗余性使得在2.5D范围数据中描述判别特征变得更加有效和高效。在本文中,将DT-CWT与线性判别分析(LDA)一起用于2.5D范围数据中,以形成拒绝分类器,该分类器可以快速消除大量候选画廊面孔。然后使用基于稀疏表示的分类来验证其余的面孔。在0.1%的FAR下,我们的方法在所有实验与所有实验中的验证率均达到98.66%。

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