A Poisson Equation-Based Method for 3D Reconstruction of Animated Images

Abstract

3D reconstruction techniques for animated images and animation techniques for faces are important research in computer graphics-related fields. Traditional 3D reconstruction techniques for animated images mainly rely on expensive 3D scanning equipment and a lot of time-consuming postprocessing manually and require the scanned animated subject to remain in a fixed pose for a considerable period. In recent years, the development of large-scale computing power of computer-related hardware, especially distributed computing, has made it possible to come up with a real-time and efficient solution. In this paper, we propose a 3D reconstruction method for multivisual animated images based on Poisson’s equation theory. The calibration theory is used to calibrate the multivisual animated images, obtain the internal and external parameters of the camera calibration module, extract the feature points from the animated images of each viewpoint by using the corner point detection operator, then match and correct the extracted feature points by using the least square median method, and complete the 3D reconstruction of the multivisual animated images. The experimental results show that the proposed method can obtain the 3D reconstruction results of multivisual animation images quickly and accurately and has certain real-time and reliability.

The Method of Reconstructing Three-Dimensional Human Posture from Two-Dimensional Images in Film and Television Production

“…The second is to generate the reconstructed three-dimensional human pose model based on the existing human body database. The third is based on two-dimensional data generated by spatial color images [ 8 ]. The first method is based on 3D human body scanning equipment for 3D human body pose reconstruction.…”