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 modulated 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.

External IDs:doi:10.1007/978-3-031-20068-7_30