Practical and Scalable Desktop-Based High-Quality Facial Capture
Alexandros Lattas, Yiming Lin, Jayanth Kannan, Ekin Ozturk, Luca Filipi, Giuseppe Claudio Guarnera, Gaurav Chawla, Abhijeet Ghosh
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."
BibTeX
@inproceedings{eccv2022_practicalandscal,
title = {Practical and Scalable Desktop-Based High-Quality Facial Capture},
author = {Alexandros Lattas and Yiming Lin and Jayanth Kannan and Ekin Ozturk and Luca Filipi and Giuseppe Claudio Guarnera and Gaurav Chawla and Abhijeet Ghosh},
booktitle = {ECCV 2022},
year = {2022}
}