Monocular Camera Video Based Reconstruction of 3D human model

Daoshun Xie, Zongyue Wang, Guorong Cai, Qiming Xia, Yidong Chen, Shengming Yang

Abstract: This paper addresses a method to obtain an accurate 3D human body model and a photorealistic free-view image of an arbitrary person from a monocular camera video. Recent works has shown that it is possible to reconstruct a human model at a level of detail from a single image. However, inferring a complete 3D human model from a network model will be ill-posed if rely on a single photograph of a person. In order to reasonably infer the 3D human model, we propose method based on implicit field representation to integrate the information of video frames by a set of structured latent code. The core of our method is to construct the implicit field by relatively sparse structured latent code. Meanwhile, align the vertices of the parametric human model and structured latent code to the same coordinate system. Extensive experimental results on monocular datasets demonstrate the effectiveness of our approach in generating accurate 3D human models. Our method utilizes a monocular camera to obtain a 3D model which enables consumers create their personality digital model.