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首页> 外文期刊>IEICE Transactions on Information and Systems >Automatic Reconstruction of 3D Human Face from CT and Color Photographs
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Automatic Reconstruction of 3D Human Face from CT and Color Photographs

机译:通过CT和彩色照片自动重建3D人脸

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摘要

This paper proposes an automatic method for reconstructing a realistic 3D facial image from CT (computer tomography) and three color photographs: front, left and right views, which can be linked easily with the underlying bone and soft tissue models. This work is the first part of our final goal, “the prediction of patient's facial appearance after cancer surgery” such as removal of a part of bone or soft tissues. The 3D facial surface derived from CT by the marching cubes algo- rithm is obviously colorless. Our task is to add the color texture of the same patient actually taken with a digital camera to the colorless 3D surface. To do this it needs an accurate registra- tion between the 3D facial image and the color photograph. Our approach is to set up a virtual camera around the 3D facial sur- face to register the virtual camera images with the corresponding color photographs by automatically adjusting seven parameters of the virtual camera. The camera parameters consists of three rotations, three translations and one scale factor. The registra- tion algorithm has been developed based upon Besl and McKay's iterative closest point (ICP) algorithm.
机译:本文提出了一种自动方法,可从CT(计算机断层扫描)和三张彩色照片(正视图,左视图和右视图)重建真实的3D面部图像,可以轻松地与基础骨骼和软组织模型关联。这项工作是我们最终目标的第一部分,即“预测癌症手术后患者的面部外观”,例如去除一部分骨骼或软组织。行进的立方体算法从CT得出的3D面部表面显然是无色的。我们的任务是将数码相机实际拍摄的同一位患者的颜色纹理添加到无色3D表面上。为此,需要在3D面部图像和彩色照片之间进行准确的注册。我们的方法是在3D面部周围设置虚拟相机,以通过自动调整虚拟相机的七个参数将虚拟相机图像与相应的彩色照片配准。摄像机参数包括三个旋转,三个平移和一个比例因子。该注册算法是基于Besl和McKay的迭代最近点(ICP)算法开发的。

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