基于单目摄像机视频的三维人体模型重建

Daoshun Xie, Zongyue Wang, Guorong Cai, Qiming Xia, Yidong Chen, S. Yang
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引用次数: 0

摘要

本文介绍了一种从单目摄像机视频中获得精确的三维人体模型和逼真的任意人的自由视场图像的方法。最近的研究表明,从单个图像中重建人体模型的细节水平是可能的。然而,如果仅仅依靠一张人的照片,从网络模型推断出一个完整的3D人体模型将是不恰当的。为了对人体三维模型进行合理的推断,提出了一种基于隐式场表示的方法,通过一组结构化的潜在代码对视频帧的信息进行整合。该方法的核心是利用相对稀疏的结构化隐码构造隐域。同时,将参数化人体模型和结构化潜码的顶点对齐到同一坐标系。在单目数据集上的大量实验结果证明了我们的方法在生成精确的3D人体模型方面的有效性。我们的方法是利用单目相机获得三维模型,使消费者能够创建自己的个性数字模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monocular Camera Video Based Reconstruction of 3D human model
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.
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