论文标题
体积视频的准确人体重建
Accurate Human Body Reconstruction for Volumetric Video
论文作者
论文摘要
在这项工作中，我们增强了专业的端到端体积视频生产管道，以仅使用被动摄像机实现高保真的人体重建。尽管当前的体积视频方法使用传统的立体声匹配技术估算了深度图，但我们介绍并优化了基于深度学习的多视图立体网络，以在专业体积视频重建的背景下进行深度图估计。此外，我们提出了一种新颖的深度图后处理方法，包括过滤和融合，考虑到光度置信度，跨视图几何一致性，前景掩码以及摄像机查看flustums。我们表明，我们的方法可以为重建的人体生成高水平的几何细节。
In this work, we enhance a professional end-to-end volumetric video production pipeline to achieve high-fidelity human body reconstruction using only passive cameras. While current volumetric video approaches estimate depth maps using traditional stereo matching techniques, we introduce and optimize deep learning-based multi-view stereo networks for depth map estimation in the context of professional volumetric video reconstruction. Furthermore, we propose a novel depth map post-processing approach including filtering and fusion, by taking into account photometric confidence, cross-view geometric consistency, foreground masks as well as camera viewing frustums. We show that our method can generate high levels of geometric detail for reconstructed human bodies.
