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3D face authentication and recognition based on bilateral symmetry analysis

机译:基于双边对称性分析的3D人脸认证与识别

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We present a novel and computationally fast method for automatic human face authentication. Taking a 3D triangular facial mesh as input, the approach first automatically extracts the bilateral symmetry plane of the facial surface. The intersection between the symmetry plane and the facial surface, namely the symmetry profile, is then computed. Using both the mean curvature plot of the facial surface and the curvature plot of the symmetry profile curve, three essential points of the nose on the symmetry profile are automatically extracted. The three essential points uniquely determine a Face Intrinsic Coordinate System (FICS). Different faces are aligned based on the FICS. The symmetry profile, together with two transverse profiles, composes a compact representation, called the SFC representation, of a 3D face surface. The face authentication and recognition steps are finally performed by comparing the SFC representations of the faces. The proposed method was tested on 382 face surfaces, which come from 166 individuals and cover a wide ethnic and age variety. The equal error rate (EER) of face authentication on scans with variable facial expressions is 10.8%. For scans with normal expression, the ERR is 0.8%.
机译:我们提出了一种新颖且计算快速的自动人脸认证方法。以3D三角形面部网格作为输入,该方法首先自动提取面部表面的双侧对称平面。然后计算对称平面和面部表面之间的交点,即对称轮廓。使用面部表面的平均曲率图和对称轮廓曲线的曲率图,可以自动提取鼻子在对称轮廓上的三个基本点。这三个基本点唯一地确定了人脸固有坐标系(FICS)。根据FICS对齐不同的面。对称轮廓与两个横向轮廓一起构成了3D面部表面的紧凑表示,称为SFC表示。最后,通过比较人脸的SFC表示来执行人脸认证和识别步骤。该方法在382个面部表面上进行了测试,这些表面来自166个个体,涵盖了广泛的种族和年龄。使用可变面部表情进行扫描时,面部认证的平均错误率(EER)为10.8%。对于具有正常表达的扫描,ERR为0.8%。

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