全局ICP与改进泊松相结合的三维人脸重建

3D face reconstruction based on global ICP and improved Poisson

为快速精确地实现人脸三维数字化,本文提出一种高精度全流程自动化的稳健三维人脸重建方法。针对基于结构光相机采集到的左右两组人脸点云和RGB图像数据,本文首先提出一种自适应下采样的全局优化ICP配准方法融合左右点云,其次提出基于法向量优化的泊松重建方法来将配准后的点云进行表面重建,生成网格化模型,该泊松重建方法针对非封闭性人脸点云有良好的重建效果和重建精度,然后将RGB图像贴图到网格化模型上,最终重建出了一个带有细节纹理的三维人脸模型。经过大量的人脸重建试验验证,本文方法具有高精度、高稳健性,能够快速、准确且稳定地重建出人脸。

In order to realize fast and accurate 3D face digitization at low cost,a high precision and robust automatic 3D face reconstruction method is proposed in this paper.Taking the left and right face point clouds and RGB image data collected by structured light camera as input,we first propose an adaptive sub-sampling global optimization ICP(iterative closest point)registration method to integrate the left and right point clouds,and then use a improved Poisson reconstruction method through normal vector optimization to reconstruct the surface of the point cloud after registration.The Poisson reconstruction method has good reconstruction effect and reconstruction accuracy for the face point cloud,which is a non-closed point cloud.Based on generated grid model,the RBG image was mapped to the mesh model,and finally a 3D face model with detailed texture is reconstructed.Extensive face reconstruction experiments demonstrate that the proposed method has the characteristics of high robustness and high precision,and can efficiently and accurately reconstruct the 3D face.