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A Coupled Statistical Model for Face Shape Recovery From Brightness Images

机译:从亮度图像恢复脸部形状的耦合统计模型

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We focus on the problem of developing a coupled statistical model that can be used to recover facial shape from brightness images of faces. We study three alternative representations for facial shape. These are the surface height function, the surface gradient, and a Fourier basis representation. We jointly capture variations in intensity and the surface shape representations using a coupled statistical model. The model is constructed by performing principal components analysis on sets of parameters describing the contents of the intensity images and the facial shape representations. By fitting the coupled model to intensity data, facial shape is implicitly recovered from the shape parameters. Experiments show that the coupled model is able to generate accurate shape from out-of-training-sample intensity images
机译:我们关注于开发可用于从面部亮度图像恢复面部形状的耦合统计模型的问题。我们研究了面部形状的三种替代表示。这些是表面高度函数,表面梯度和傅立叶基础表示。我们使用耦合的统计模型共同捕获强度和表面形状表示形式的变化。通过对描述强度图像和面部形状表示内容的参数集执行主成分分析来构建模型。通过将耦合模型拟合到强度数据,可以从形状参数中隐式恢复脸部形状。实验表明,耦合模型能够从训练样本外的强度图像中生成准确的形状

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