Reconstructing Three-Dimensional Human Poses: A Combined Approach of Iterative Calculation on Skeleton Model and Conformal Geometric Algebra.

Reconstructing three-dimensional (3D) human poses is an essential step in human body animation. The purpose of this paper is to fill the gap in virtual reality research by reconstructing postures in a high-precision human model. This paper presents a new approach for 3D human pose reconstruction based on the iterative calculation of a skeleton model and conformal geometric algebra, captured by a monocular camera. By introducing the strip information of clothes and prior data of different human limbs, the location of joint points on the human body will not be affected by the occlusion problem. We then calculate the 3D coordinates of joint points based on the proposed method of the iterative calculation of the skeleton model, which can solve the high-cost problem caused by the need for multiple cameras or a depth camera. Subsequently, we utilize high-performance conformal geometric algebra (CGA) in relation to rotation transformations in order to improve the adjustment of the postures of the human limbs. Finally, realistic 3D human poses are reconstructed-specifically, the motion of the human limbs-using a rigid transformation of CGA and a smooth connection of the limb parts based on a high-precision model. Compared with the existing methods, the proposed approach can obtain satisfactory and realistic 3D human pose estimation results using grid models.