People Snapshot Dataset

Video Based Reconstruction of 3D People Models

Thiemo Alldieck¹, Marcus Magnor¹, Weipeng Xu², Christian Theobalt² and Gerard Pons-Moll²
¹Computer Graphics Lab, TU Braunschweig ²Max Planck Institute for Informatics, Saarland Informatics Campus

CVPR 2018 (spotlight), Salt Lake City, USA

Abstract

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.

Source Code

License

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Dataset

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License

Please read carefully the following terms and conditions and any accompanying documentation before you download and/or use the People-Snapshot dataset, (the “Dataset”).

The authors grant you a non-exclusive, non-transferable, free of charge right:

To download the Dataset and use it on computers owned, leased or otherwise controlled by you and/or your organisation;
To use the Dataset for the sole purpose of performing non-commercial scientific research, non-commercial education, or non-commercial artistic projects.

Without prior written approval from the authors, the Dataset, in whole or in part, shall not be further distributed, published, copied, or disseminated in any way or form whatsoever, whether for profit or not. This includes further distributing, copying or disseminating to a different facility or organizational unit in the requesting university, organization, or company.

THE DATASET IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE DATASET OR THE USE OR OTHER DEALINGS IN THE DATASET.

You understand and agree that the authors are under no obligation to provide either maintenance services, update services, notices of latent defects, or corrections of defects with regard to the Dataset. The authors nevertheless reserve the right to update, modify, or discontinue the Dataset at any time.

You agree to cite the Video Based Reconstruction of 3D People Models paper in documents and papers that report on research using this Dataset.

I have read and agree the above license.

I use Code & Dataset for the sole purpose of performing non-commercial scientific research, non-commercial education, or non-commercial artistic projects.

Paper

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}
}