Practical and Scalable Desktop-based High Quality Facial Capture
European Conference on Computer Vision (ECCV) 2022 (oral)
Alexandros Lattas ² Yiming Lin ¹ Jayanth Kannan ¹ Ekin Ozturk ¹ ² Luca Filipi ¹ Giuseppe Claudio Guarnera¹ ³ Gaurav Chawla ¹ Abhijeet Ghosh ¹ ²
Imperial College London ²
University of York ³
Patent Pending
Fig. 1: Two proposed novel desktop-based setups (a, c) for high-quality facial capture (b, d). Left: setup consisting of a set of portable mobile devices – tablets and smartphones, for static facial capture. Right: setup consisting of a set desktop LCD displays for static and dynamic 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 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.
Publication: Practical and Scalable Desktop-based High Quality Facial Capture. Alexandros Lattas, Yiming Lin, Jayanth Kannan, Ekin Ozturk, Luca Filipi, Giuseppe Claudio Guarnera, Gaurav Chawla, and Abhijeet Ghosh. European Conference on Computer Vision (ECCV), October 2022. (oral, Patent Pending)
