Video Based Reconstruction of 3D People Models
Video Based Reconstruction of 3D People Models
复制标题
DOI：
10.1109/cvpr.2018.00875
复制
发表时间：
2018-03
期刊：
影响因子：
--
通讯作者：
Thiemo Alldieck;M. Magnor;Weipeng Xu;C. Theobalt;Gerard Pons-Moll
中科院分区：
文献类型：
--
作者：
Thiemo Alldieck;M. Magnor;Weipeng Xu;C. Theobalt;Gerard Pons-Moll
本文描述了一种方法，以获得准确的三维身体模型和纹理的任意人从一个单一的，单目视频中的一个人正在移动。基于一个参数化的身体模型，我们提出了一个强大的处理流水线来推断3D模型形状，包括穿着衣服的人与4.5mm的重建精度。我们的方法的核心是将动态身体姿势转换为规范的参考系。我们的主要贡献是一种方法来转换对应于动态人体轮廓的轮廓锥，以获得一个共同的参考系中的视觉船体。这使得能够基于大量帧有效地估计一致的3D形状、纹理和植入的动画骨架。在4个不同数据集上的结果证明了我们的方法在生成精确的3D模型方面的有效性。我们的方法只需要一个RGB摄像头，每个人都可以创建自己的完全动画数字替身，例如，用于社交VR应用或在线时尚购物的虚拟试穿。
This paper describes a method to obtain accurate 3D body models and texture of arbitrary people from a single, monocular video in which a person is moving. Based on a parametric body model, we present a robust processing pipeline to infer 3D model shapes including clothed people with 4.5mm reconstruction accuracy. At the core of our approach is the transformation of dynamic body pose into a canonical frame of reference. Our main contribution is a method to transform the silhouette cones corresponding to dynamic human silhouettes to obtain a visual hull in a common reference frame. This enables efficient estimation of a consensus 3D shape, texture and implanted animation skeleton based on a large number of frames. Results on 4 different datasets demonstrate the effectiveness of our approach to produce accurate 3D models. Requiring only an RGB camera, our method enables everyone to create their own fully animatable digital double, e.g., for social VR applications or virtual try-on for online fashion shopping.