This paper introduces an automated 3D-reconstruction method for generating high-quality virtual humans from monocular smartphone cameras. The input of our approach are two video clips, one capturing the whole body and the other providing detailed close-ups of head and face. Optical flow analysis and sharpness estimation select individual frames, from which two dense point clouds for the body and head are computed using multi-view reconstruction. Automatically detected landmarks guide the fitting of a virtual human body template to these point clouds, thereby reconstructing the geometry. A graph-cut stitching approach reconstructs a detailed texture. Our results are compared to existing low-cost monocular approaches as well as to expensive multi-camera scan rigs. We achieve visually convincing reconstructions that are almost on par with complex camera rigs while surpassing similar low-cost approaches. The generated high-quality avatars are ready to be processed, animated, and rendered by standard XR simulation and game engines such as Unreal or Unity
%0 Conference Paper
%1 conf/vrst/WenningerABLB20
%A Wenninger, Stephan
%A Achenbach, Jascha
%A Bartl, Andrea
%A Latoschik, Marc Erich
%A Botsch, Mario
%B VRST
%D 2020
%E Teather, Robert J.
%E Joslin, Chris
%E Stuerzlinger, Wolfgang
%E Figueroa, Pablo
%E Hu, Yaoping
%E Batmaz, Anil Ufuk
%E Lee, Wonsook
%E Ortega, Francisco
%I ACM
%K emlab myown via-vr vitras
%P 29:1-29:11
%T Realistic Virtual Humans from Smartphone Videos.
%U https://dl.acm.org/doi/pdf/10.1145/3385956.3418940
%X This paper introduces an automated 3D-reconstruction method for generating high-quality virtual humans from monocular smartphone cameras. The input of our approach are two video clips, one capturing the whole body and the other providing detailed close-ups of head and face. Optical flow analysis and sharpness estimation select individual frames, from which two dense point clouds for the body and head are computed using multi-view reconstruction. Automatically detected landmarks guide the fitting of a virtual human body template to these point clouds, thereby reconstructing the geometry. A graph-cut stitching approach reconstructs a detailed texture. Our results are compared to existing low-cost monocular approaches as well as to expensive multi-camera scan rigs. We achieve visually convincing reconstructions that are almost on par with complex camera rigs while surpassing similar low-cost approaches. The generated high-quality avatars are ready to be processed, animated, and rendered by standard XR simulation and game engines such as Unreal or Unity
%@ 978-1-4503-7619-8
@inproceedings{conf/vrst/WenningerABLB20,
abstract = {This paper introduces an automated 3D-reconstruction method for generating high-quality virtual humans from monocular smartphone cameras. The input of our approach are two video clips, one capturing the whole body and the other providing detailed close-ups of head and face. Optical flow analysis and sharpness estimation select individual frames, from which two dense point clouds for the body and head are computed using multi-view reconstruction. Automatically detected landmarks guide the fitting of a virtual human body template to these point clouds, thereby reconstructing the geometry. A graph-cut stitching approach reconstructs a detailed texture. Our results are compared to existing low-cost monocular approaches as well as to expensive multi-camera scan rigs. We achieve visually convincing reconstructions that are almost on par with complex camera rigs while surpassing similar low-cost approaches. The generated high-quality avatars are ready to be processed, animated, and rendered by standard XR simulation and game engines such as Unreal or Unity},
added-at = {2020-11-05T07:32:24.000+0100},
author = {Wenninger, Stephan and Achenbach, Jascha and Bartl, Andrea and Latoschik, Marc Erich and Botsch, Mario},
biburl = {https://www.bibsonomy.org/bibtex/284ed6d2c6762d11e29e4de114f5032c7/hci-uwb},
booktitle = {VRST},
crossref = {conf/vrst/2020},
editor = {Teather, Robert J. and Joslin, Chris and Stuerzlinger, Wolfgang and Figueroa, Pablo and Hu, Yaoping and Batmaz, Anil Ufuk and Lee, Wonsook and Ortega, Francisco},
ee = {https://doi.org/10.1145/3385956.3418940},
interhash = {f08bfebf60917fcc94f4f836171b0b53},
intrahash = {84ed6d2c6762d11e29e4de114f5032c7},
isbn = {978-1-4503-7619-8},
keywords = {emlab myown via-vr vitras},
note = {Best paper award 🏆},
pages = {29:1-29:11},
publisher = {ACM},
timestamp = {2024-11-21T09:27:11.000+0100},
title = {Realistic Virtual Humans from Smartphone Videos.},
url = {https://dl.acm.org/doi/pdf/10.1145/3385956.3418940},
year = 2020
}