Abstract : We present a fully automated algorithm for facial feature extraction and 3D face modeling from a pair of orthogonal frontal and profile view images of a person’s face taken by calibrated cameras. The algorithm starts by automatically extracting corresponding 2D landmark facial features from both view images, then compute their 3D coordinates. Further, we estimate the coordinates of the features that are hidden in the profile view based on the visible features extracted in the two orthogonal face images. The 3D coordinates of the selected feature points obtained from the images are used first to align, then to locally deform the corresponding facial vertices of the generic 3D model. Preliminary experiments to assess the applicability of the applicability of the resulted models for face recognition show encouraging results.
文摘:提出一种全自动面部特征提取算法模型和三维人脸从侧面和正面的正交的人的脸被标定相机。自动提取算法进行了相应的二维划时代的面部特征,然后从浏览图像的三维坐标计算。进一步,我们估计坐标的特征,是隐藏在地震剖面视图特征提取的基础上两可见正交脸孔图像。这个点的三维坐标选定的特征点的图像是用从第一,然后到当地的顶点对应的变形的面部三维模型的一般。初步实验中的适用性评价模型的适用性,显示了人脸识别结果令人满意。
人工翻译:
摘要:我们现在从正面和剖面正交校准相机拍摄的由一个人的脸浏览图片对一个人脸特征提取和三维人脸建模完全自动化的算法。该算法通过自动提取相应的二维图像都认为具有里程碑意义的面部特征,然后计算其三维坐标启动。此外,我们估计的是,对在两个正交人脸图像特征提取的基础上可见隐藏的功能配置视图坐标。三维坐标从图像中选定的功能得到点首先用于对齐,然后到当地的一般变形的三维模型的相应面部顶点。初步的试验,以评估对人脸识别的令人鼓舞的结果表明,导致模型的适用性适用性。