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

Xin Huang,Lei Gao

doi:10.3390/sym11030301

Abstract

Reconstructing three-dimensional (3D) human poses is an essential step in human bodyanimation. The purpose of this paper is to fill the gap in virtual reality research by reconstructingpostures in a high-precision human model. This paper presents a new approach for 3D human posereconstruction 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 ofdifferent human limbs, the location of joint points on the human body will not be affected by theocclusion problem. We then calculate the 3D coordinates of joint points based on the proposed methodof the iterative calculation of the skeleton model, which can solve the high-cost problem caused by theneed for multiple cameras or a depth camera. Subsequently, we utilize high-performance conformalgeometric algebra (CGA) in relation to rotation transformations in order to improve the adjustmentof 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 ofthe limb parts based on a high-precision model. Compared with the existing methods, the proposedapproach can obtain satisfactory and realistic 3D human pose estimation results using grid models.

Highlights

With the continuous advance and gradual maturity of computer sciences, humans expect to obtain and deal with more information about themselves by means of computer technology, such as tracking human limb motion
To test the proposed location of the joint points in the target human body images and 3D human pose reconstruction, the experiments were implemented based on the captured human body images and motion sequences for different human poses
In order to avoid the phenomenon of the labels not being able to indicate the correct joint positions when the human pose is changed, another person helped to adjust the positions of all the labels when the target human body was located in corresponding poses

Summary

Introduction

With the continuous advance and gradual maturity of computer sciences, humans expect to obtain and deal with more information about themselves by means of computer technology, such as tracking human limb motion As it contains personality and gait characteristics, human motion plays an important role in various fields of application, such as posture analysis and virtual reality. 3D human posture estimation based on monocular video sequences has received more attention, owing to its advantages of low cost and less limitations. The applications have their special requirements for 3D human pose estimation, two key performance indicators for human pose estimation algorithms are accuracy and real-time. Stommel et al [5] proposed a novel method for estimating 3D human poses based on the spatiotemporal segmentation of key points, provided by depth contours, using Kinect

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