图像驱动的三维人脸自动生成与编辑算法

针对图像驱动的三维人脸建模这个计算机图形学中的研究热点问题,提出一种采用三维人脸形变模型的三维人脸自动生成与编辑算法.首先建立三维人脸形变模型,由三维人脸数据库统计学习得到线性混合人脸模型,用一个低维的参数向量来描述一个人脸;然后通过人脸检测、人脸对齐、边缘提取等方法从人脸图像中提取人脸的特征,根据这些特征实现三维人脸形变模型与图像的匹配,重建出与图像对应的三维人脸模型;最后,通过改变参数向量的值实现人脸的编辑.对5个输入人脸照片进行了三维人脸模型重建和编辑并且将重建的人脸模型和真实人脸模型进行了对比,实验结果表明,该算法可实现真实化的人脸重建效果.

Image-Driven Automatic 3D Human Face Modeling and Editing Algorithm

Image-driven 3D face modeling is a hot topic in computer graphics.This paper proposes an image driven automatic 3D human face modeling and editing algorithm,which is based on a 3D morphable face model.The 3D morphable face model is a blended shape model built through statistical learning from a 3D face database,through which a face can be represented by a low-dimensional parameter vector.Our method extracts the image features by the algorithms of face detection,face alignment and edge extraction,and then fits the 3D morphable face model with the image to reconstruct the corresponding 3D face model.Furthermore,the 3D face model can be edited by adjusting the parameter vector.The algorithm is verified by inputting 5 face pictures and reconstructing 3D face models,and then comparing the results between the real face model and the reconstructed model.The comparison results show that this method can generate realistic 3D human face and edit the face model with various styles.