Realistic 3D head reconstruction based on feature points matching between photo images and 3D generic model
匹配图像与3维模型特征点的真实感3维头重建

We proposes a framework for reconstructing one 3D head model based on two orthogonal images and one 3D generic head model through feature matching. First, we segment the images into face and hair regions. For frontal images, feature points are located by an improved ASM (active shape model), for side images, feature points are found by an improved local maximum curvature tracking method. In this method, we select some distinctive feature points from the generic 3D model. These 3D feature points are matched to the detected image feature points. Based on the radical basis function (RBF), the generic 3D model is morphed, and the shape model is obtained. Since the images from orthogonal views may have different illumination, color transfer is used to enforce the texture color consistency. Based on the shape model, these two images are matched, and one seamless texture is generated. The final head reconstruction is achieved by mapping the texture to the 3D head model.