Authors
Abhijeet Ghosh, Graham Fyffe, Borom Tunwattanapong, Jay Busch, Xueming Yu, Paul Debevec
USC Institute for Creative Technologies
Portals
Summary
This paper presents a new pair of linearly polarized lighting patterns to enable multiview diffuse-specular separation. With the albedo and normal maps as input, a novel multi-resolution adaptive domain message passing stereo reconstruction algorithm is proposed to create high-resolution facial geometry.
Abstract
We present a novel process for acquiring detailed facial geometry with high resolution diffuse and specular photometric information from multiple viewpoints using polarized spherical gradient illumination. Key to our method is a new pair of linearly polarized lighting patterns which enables multiview diffuse-specular separation under a given spherical illumination condition from just two photographs. The patterns -- one following lines of latitude and one following lines of longitude -- allow the use of fixed linear polarizers in front of the cameras, enabling more efficient acquisition of diffuse and specular albedo and normal maps from multiple viewpoints. In a second step, we employ these albedo and normal maps as input to a novel multi-resolution adaptive domain message passing stereo reconstruction algorithm to create high resolution facial geometry. To do this, we formulate the stereo reconstruction from multiple cameras in a commonly parameterized domain for multiview reconstruction. We show competitive results consisting of high-resolution facial geometry with relightable reflectance maps using five DSLR cameras. Our technique scales well for multiview acquisition without requiring specialized camera systems for sensing multiple polarization states.
Contribution
- A new polarized spherical gradient illumination technique which enables multiview face scanning
- A demonstration of multiview acquisition employing low-cost, static polarizers on both the cameras and light sources
- A novel multi-resolution adaptive domain message passing stereo reconstruction algorithm which uses diffuse and specular albedo and normal maps for high quality facial geometry reconstruction
Related Works
3D Facial Capture; Spherical Gradient Illumination
Comparisons
Fyffe et al.
Overview
Our multiview geometry reconstruction algorithm takes the acquired diffuse and specular albedo and normal maps from each of the cameras and derives a high resolution face mesh. We calibrate our cameras in a common coordinate system for stereo reconstruction.