A Method for Enforcing Integrability in Shape from Shading Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Spacetime faces: high resolution capture for modeling and animation
ACM SIGGRAPH 2004 Papers
Silhouette and stereo fusion for 3D object modeling
Computer Vision and Image Understanding - Model-based and image-based 3D scene representation for interactive visalization
Efficiently combining positions and normals for precise 3D geometry
ACM SIGGRAPH 2005 Papers
A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Photometric Stereo with General, Unknown Lighting
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Facial performance synthesis using deformation-driven polynomial displacement maps
ACM SIGGRAPH Asia 2008 papers
Shadows in Three-Source Photometric Stereo
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Photometric stereo for dynamic surface orientations
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Rapid acquisition of specular and diffuse normal maps from polarized spherical gradient illumination
EGSR'07 Proceedings of the 18th Eurographics conference on Rendering Techniques
Lightweight binocular facial performance capture under uncontrolled lighting
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Robust 3D face capture using example-based photometric stereo
Computers in Industry
Real-time recovery of moving 3D faces for emerging applications
Computers in Industry
| Hi-index | 0.00 |
This paper addresses the problem of obtaining 3d detailed reconstructions of human faces in real-time and with inexpensive hardware. We present an algorithm based on a monocular multi-spectral photometric-stereo setup. This system is known to capture high-detailed deforming 3d surfaces at high frame rates and without having to use any expensive hardware or synchronized light stage. However, the main challenge of such a setup is the calibration stage, which depends on the lights setup and how they interact with the specific material being captured, in this case, human faces. For this purpose we develop a self-calibration technique where the person being captured is asked to perform a rigid motion in front of the camera, maintaining a neutral expression. Rigidity constrains are then used to compute the head's motion with a structure-from-motion algorithm. Once the motion is obtained, a multi-view stereo algorithm reconstructs a coarse 3d model of the face. This coarse model is then used to estimate the lighting parameters with a stratified approach: In the first step we use a RANSAC search to identify purely diffuse points on the face and to simultaneously estimate this diffuse reflectance model. In the second step we apply non-linear optimization to fit a non-Lambertian reflectance model to the outliers of the previous step. The calibration procedure is validated with synthetic and real data.