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Expression-Compensated 3D Face Recognition with Geodesically Aligned Bilinear Models

机译:表达式补偿3D面部识别与大量对齐的双线性模型

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In this paper, we present a technique for addressing 3-dimensional face recognition in presence of facial expressions using a bilinear model. The bilinear model allows decoupling the impact of identity and expression on face appearance and encoding their contribution in separate control parameters. This is achieved by first representing faces as parametric surface models described by a fixed length parameter vector. A generic face model is fitted to each face based on a novel technique that relies on geodesic distances to find implicitly corresponding facial landmarks between the model and the face in hand. Model parameters are then used for bilinear decomposition. The experimental results on the publicly available BU-3DFE face database demonstrate the effectiveness of our technique.
机译:在本文中,我们介绍了一种用双线性模型在面部表达式存在下解决三维人脸识别的技术。双线性模型允许在脸部外观上解耦并在单独的控制参数中对其贡献进行解耦。这是通过首先将面作为由固定长度参数向量描述的参数表面模型来实现的。基于依赖于测地距的新技术,将通用面部模型安装在每个面上,以依赖于测地距,以在手中的模型和面部之间找到隐式相应的面部地标。然后用于模型参数用于双线性分解。公开的BU-3DFE面部数据库的实验结果证明了我们技术的有效性。

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