Abstract摘要
In this paper, a new technique for modeling textured 3D faces is introduced. 3D faces can either be generated automatically from one or more photographs, or modeled directly through an intuitive user interface. Users are assisted in two key problems of computer aided face modeling. First, new face images or new 3D face models can be registered automatically by computing dense one-to-one correspondence to an internal face model. Second, the approach regulates the naturalness of modeled faces avoiding faces with an “unlikely” appearance.
本文介绍了一种新的三维纹理人脸建模技术。三维面可以从一张或多张照片自动生成，也可以通过直观的用户界面直接建模。计算机辅助人脸建模的两个关键问题是辅助用户。首先，通过计算与内部人脸模型的密集一一对应关系，可以自动注册新的人脸图像或新的三维人脸模型。其次，该方法规范了模拟人脸的自然性，避免了具有“不太可能”外观的人脸。
Starting from an example set of 3D face models, we derive a morphable face model by transforming the shape and texture of the examples into a vector space representation. New faces and expressions can be modeled by forming linear combinations of the prototypes. Shape and texture constraints derived from the statistics of our example faces are used to guide manual modeling or automated matching algorithms.
从一组三维人脸模型的实例出发，通过将实例的形状和纹理转化为矢量空间表示，得到了一个可变形的人脸模型。新的面和表达式可以通过形成原型的线性组合来建模。从我们的示例面统计信息中导出的形状和纹理约束用于指导手动建模或自动匹配算法。
We show 3D face reconstructions from single images and their applications for photo-realistic image manipulations. We also demonstrate face manipulations according to complex parameters such as gender, fullness of a face or its distinctiveness.
我们展示了由单个图像重建的三维人脸及其在照片真实感图像处理中的应用。我们还展示了根据复杂的参数，如性别，面部丰满度或其独特性的面部操作。
1 Introduction
Computer aided modeling of human faces still requires a great deal of expertise and manual control to avoid unrealistic, non-face-like results. Most limitations of automated techniques for face synthesis, face animation or for general changes in the appearance of an individual face can be described either as the problem of finding corresponding feature locations in different faces or as the problem of separating realistic faces from faces that could never appear in the real world. The correspondence problem is crucial for all morphing techniques, both for the application of motion-capture data to pictures or 3D face models, and for most 3D face reconstruction techniques from images. A limited number of labeled feature points marked in one face, e.g., the tip of the nose, the eye corner and less prominent points on the cheek, must be located precisely in another face. The number of manually labeled feature points varies from
计算机辅助人脸建模仍然需要大量的专业知识和手动控制，以避免不现实的、非人脸的结果。用于人脸合成、人脸动画或单个人脸外观的一般变化的自动化技术的大多数局限性可以描述为在不同的人脸中找到相应的特征位置的问题，或者描述为将真实的人脸与现实世界中永远不会出现的面分离的问题。无论是对于将运动捕捉数据应用于图片或三维人脸模型，还是对于大多数基于图像的三维人脸重建技术，对应问题对于所有变形技术都是至关重要的。在一张脸上标记的有限数量的标记特征点，例如鼻尖、眼角和脸颊上不太突出的点，必须精确地位于另一张脸上。手动标记的特征点的数目从