Accurate Human Body Reconstruction for Volumetric Video

• URL: http://arxiv.org/abs/2202.13118v1
• Date: Sat, 26 Feb 2022 11:37:08 GMT
• Title: Accurate Human Body Reconstruction for Volumetric Video
• Authors: Decai Chen, Markus Worchel, Ingo Feldmann, Oliver Schreer, Peter Eisert
• Abstract summary: We introduce and optimize deep learning-based multi-view stereo networks for depth map estimation in the context of professional volumetric video reconstruction. We show that our method can generate high levels of geometric detail for reconstructed human bodies.
• Score: 0.9134661726886928
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: 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.

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