Reserach On 3D Human Pose Estimation For A Single Image

When reconstructing 3D human pose based on 2D human joint point coordinates in images,a nonconvex optimization problem is often encountered.It brings great difficulties to the solution of human pose.Although the convex relaxation approach for 3D human pose estimation has been solved this problem,its convergence speed is slow and accuracy of human pose estimation is not high.To overcome these shortcomings,this article proposes an adaptive convex relaxation approach based on genetic optimization for 3D human pose estimation.Firstly,adaptive processing is performed on the variable which controls iterative step in the original convex relaxation approach by using error evaluation function according to the idea of adaptive control.Then it uses the Genetic Algorithm to optimize initial value of the variable.Finally it improves the expression of closed-form solution in the original convex relaxation approach by using the result of optimization.The experimental results show that the improved 3D human pose estimation algorithm has faster speed and higher accuracy of human pose estimation results when processing single human image,which could be more beneficial to practical applications.