Video Based Reconstruction of 3D People Models

This paper describes how 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 achieving 3D model fits with 5mm accuracy also for clothed people. Our main contribution is a method to nonrigidly deform the silhouette cones corresponding to the dynamic human silhouettes, resulting in a visual hull in a common reference frame that enables surface reconstruction. This enables efficient estimation of a consensus 3D shape, texture and implanted animation skeleton based on a large number of frames. We present evaluation results for a number of test subjects and analyze overall performance. Requiring only a smartphone or webcam, 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.
Code & Dataset
Download code and dataset here.
In Press
- Article on sciencemag.org
- Article on golem.de (german)
- Video on ScienceChannel
Author(s): | Thiemo Alldieck, Marcus Magnor, Weipeng Xu, Christian Theobalt, Gerard Pons-Moll |
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Published: | June 2018 |
Type: | Article in conference proceedings |
Book: | IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (IEEE) |
ISBN: | 978-1-5386-6420-9 |
DOI: | 10.1109/CVPR.2018.00875 |
Presented at: | Conference on Computer Vision and Pattern Recognition (CVPR) 2018 |
Note: | CVPR Spotlight Paper |
Project(s): | Comprehensive Human Performance Capture from Monocular Video Footage Immersive Digital Reality |
BibTex PDF Link Suppl. Material Code Video arXiv
@inproceedings{alldieck2018video, title = {Video Based Reconstruction of 3D People Models}, author = {Alldieck, Thiemo and Magnor, Marcus and Xu, Weipeng and Theobalt, Christian and Pons-Moll, Gerard}, booktitle = {{IEEE}/{CVF} Conference on Computer Vision and Pattern Recognition ({CVPR})}, isbn = {978-1-5386-6420-9}, doi = {10.1109/{CVPR}.2018.00875}, note = {{CVPR} Spotlight Paper}, pages = {8387--8397}, month = {Jun}, year = {2018} }
Authors
Thiemo Alldieck
Fmr. ResearcherMarcus Magnor
Director, ChairWeipeng Xu
ExternalChristian Theobalt
ExternalGerard Pons-Moll
External