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    • 10. 发明授权
    • System and method for face recognition using synthesized images
    • 使用合成图像进行人脸识别的系统和方法
    • US07095879B2
    • 2006-08-22
    • US11053337
    • 2005-02-07
    • Jie YanHong-Jiang Zhang
    • Jie YanHong-Jiang Zhang
    • G06K9/00G06T15/00
    • G06T17/00G06K9/00288G06K9/6256
    • A system and method that includes a virtual human face generation technique which synthesizes images of a human face at a variety of poses. This is preferably accomplished using just a frontal and profile image of a specific subject. An automatic deformation technique is used to align the features of a generic 3-D graphic face model with the corresponding features of these pre-provided images of the subject. Specifically, a generic frontal face model is aligned with the frontal image and a generic profile face model is aligned with the profile image. The deformation procedure results in a single 3-D face model of the specific human face. It precisely reflects the geometric features of the specific subject. After that, subdivision spline surface construction and multi-direction texture mapping techniques are used to smooth the model and endow photometric detail to the specific 3-D geometric face model. This smoothed and texturized specific 3-D face model is then used to generate 2-D images of the subject at a variety of face poses. These synthesized face images can be used to build a set of training images that may be used to train a recognition classifier.
    • 一种包括以各种姿势合成人脸图像的虚拟人脸生成技术的系统和方法。 这优选仅使用特定对象的正面和轮廓图像来完成。 使用自动变形技术将通用3-D图形面部模型的特征与对象的这些预先提供的图像的对应特征对齐。 具体来说,通常的正面面部模型与正面图像对准,并且通用轮廓面部模型与轮廓图像对准。 变形过程导致特定人脸的单个3-D面部模型。 它精确地反映了具体主题的几何特征。 之后,使用细分花键表面构造和多向纹理映射技术来平滑模型,并将光度细节赋予特定的3-D几何面模型。 然后使用这种平滑和纹理化的特定3-D面部模型在各种脸部姿势下产生受试者的2-D图像。 这些合成的面部图像可以用于构建可用于训练识别分类器的一组训练图像。