A Method for Enforcing Integrability in Shape from Shading Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Approximate nearest neighbors: towards removing the curse of dimensionality
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
International Journal of Computer Vision
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Detection in Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lambertian Reflectance and Linear Subspaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bases for Non-homogeneous Polynomial Ck Splines on the Sphere
LATIN '98 Proceedings of the Third Latin American Symposium on Theoretical Informatics
Shape and albedo from multiple images using integrability
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Photometric Stereo via Locality Sensitive High-Dimension Hashing
CRV '05 Proceedings of the 2nd Canadian conference on Computer and Robot Vision
Example-Based Photometric Stereo: Shape Reconstruction with General, Varying BRDFs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combinatorial Surface Integration
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Photometric Stereo with General, Unknown Lighting
International Journal of Computer Vision
Facial Shape-from-shading and Recognition Using Principal Geodesic Analysis and Robust Statistics
International Journal of Computer Vision
Matching Photometric Observation Vectors with Shadows and Variable Albedo
SIBGRAPI '08 Proceedings of the 2008 XXI Brazilian Symposium on Computer Graphics and Image Processing
A survey of approaches and challenges in 3D and multi-modal 3D+2D face recognition
Computer Vision and Image Understanding
Shape and Spatially-Varying BRDFs from Photometric Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D face reconstructions from photometric stereo using near infrared and visible light
Computer Vision and Image Understanding
Robust 3D Face Recognition by Local Shape Difference Boosting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Photometric stereo from maximum feasible Lambertian reflections
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Single-shot photometric stereo by spectral multiplexing
ACM SIGGRAPH ASIA 2010 Sketches
3D Face Recognition Using Isogeodesic Stripes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape and materials by example: a photometric stereo approach
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
What is the range of surface reconstructions from a gradient field?
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Self-calibrated, Multi-spectral Photometric Stereo for 3D Face Capture
International Journal of Computer Vision
Multi-scale integration of slope data on an irregular mesh
PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part I
Face detection using quantized skin color regions merging andwavelet packet analysis
IEEE Transactions on Multimedia
A robust multi-scale integration method to obtain the depth from gradient maps
Computer Vision and Image Understanding
Face recognition in 2D and 2.5D using ridgelets and photometric stereo
Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Uniform Grid Structure to Speed Up Example-Based Photometric Stereo
IEEE Transactions on Image Processing
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We show that using example-based photometric stereo, it is possible to achieve realistic reconstructions of the human face. The method can handle non-Lambertian reflectance and attached shadows after a simple calibration step. We use spherical harmonics to model and de-noise the illumination functions from images of a reference object with known shape, and a fast grid technique to invert those functions and recover the surface normal for each point of the target object. The depth coordinate is obtained by weighted multi-scale integration of these normals, using an integration weight mask obtained automatically from the images themselves. We have applied these techniques to improve the PhotoFace system of Hansen et al. (2010).