Practical and Scalable Desktop-Based High-Quality Facial Capture
Abstract
We present a novel desktop-based system for high-quality facial capture including geometry and facial appearance. The proposed acquisition system is highly practical and scalable, consisting purely of commodity components. The setup consists of a set of displays for controlled illumination for reflectance capture, in conjunction with multiview acquisition of facial geometry. We additionally present a novel set of binary illumination patterns for efficient acquisition of reflectance and photometric normals using our setup, with diffuse-specular separation. We demonstrate high-quality results with two different variants of the capture setup - one entirely consisting of portable mobile devices targeting static facial capture, and the other consisting of desktop LCD displays targeting both static and dynamic facial capture.
Cite
Text
Lattas et al. "Practical and Scalable Desktop-Based High-Quality Facial Capture." Proceedings of the European Conference on Computer Vision (ECCV), 2022. doi:10.1007/978-3-031-20068-7_30Markdown
[Lattas et al. "Practical and Scalable Desktop-Based High-Quality Facial Capture." Proceedings of the European Conference on Computer Vision (ECCV), 2022.](https://mlanthology.org/eccv/2022/lattas2022eccv-practical/) doi:10.1007/978-3-031-20068-7_30BibTeX
@inproceedings{lattas2022eccv-practical,
title = {{Practical and Scalable Desktop-Based High-Quality Facial Capture}},
author = {Lattas, Alexandros and Lin, Yiming and Kannan, Jayanth and Ozturk, Ekin and Filipi, Luca and Guarnera, Giuseppe Claudio and Chawla, Gaurav and Ghosh, Abhijeet},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2022},
doi = {10.1007/978-3-031-20068-7_30},
url = {https://mlanthology.org/eccv/2022/lattas2022eccv-practical/}
}