Research On Reconstruction Algorithm Of 3D Dressed Human Body Based On 2D Image

Reconstructing a three-dimensional human body model wearing clothing from a single image is an important research topic in the field of computer vision,such as VR,3D games,virtual fitting,and so on.This paper presents a method that uses a single two-dimensional RGB image as input to reconstruct a dressed human body in a natural background,and quickly produces a three-dimensional human body model wearing clothing.The method consists of three stages.The first stage designs an instance segmentation method that optimizes boundary pixels to accurately extract the foreground mask of the human body from the natural background.The second stage designs a non-parametric method for reconstructing the three-dimensional human body mesh model based on implicit functions,combined with end-to-end prediction of highquality three-dimensional human body mesh using the foreground mask of the human body.The third stage develops a texture renderer that quickly renders a three-dimensional human body mesh model with clothing texture.Overall,the main research work and contributions of this paper are shown as follows:(1)This paper designs a high-quality instance segmentation method for complex backgrounds.In order to solve the problem that the current mainstream instance segmentation methods exhibit rough and sticky behavior at the edges of the target,this paper improves on the Mask R-CNN network structure by introducing a semantic branch to provide detailed semantic information and high-quality semantic masks.Then,an arithmetic operation mechanism is designed to extract the target boundary and select uncertain points from it.Finally,uncertain points are predicted based on semantic and instance features to refine the target boundary and improve robustness.(2)This paper proposes an implicit function method for reconstructing a three-dimensional human body mesh model from a single image on the Pa MIR network structure.First,in response to the issue that the current implicit function methods have poor model detail and pose robustness in outdoor environments,this paper introduces signed distance function(SDF)and normal maps to improve the encoding of 3D query points.Second,a hierarchical voxel encoding network is designed that further reduces the error in the shape structure of the reconstructed threedimensional human body mesh model by obtaining volume features from the SMPL parametric model from coarse to fine.(3)This paper develops a texture renderer based on Direct X11.Firstly,a color vector is added to the vertices of the three-dimensional human body mesh model through UV mapping.Then,the texture renderer is used to parse the mesh model data and quickly render a 3D clothed human body model.