A Method for Enforcing Integrability in Shape from Shading Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Illuminant Direction, Albedo, and Shape from Shading
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Photometric Issues in 3D Visual Recognition from aSingle 2D Image
International Journal of Computer Vision
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Linear Object Classes and Image Synthesis From a Single Example Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
What Is the Set of Images of an Object Under All Possible Illumination Conditions?
International Journal of Computer Vision
International Journal of Computer Vision
International Journal of Computer Vision
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Reconstruction of 3D Bilaterally Symmetric Surfaces
International Journal of Computer Vision - Special issue on computer vision research at the Technion
The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Linear fitting with missing data for structure-from-motion
Computer Vision and Image Understanding
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
Symmetric Shape-from-Shading Using Self-ratio Image
International Journal of Computer Vision
Principal Component Analysis with Missing Data and Its Application to Polyhedral Object Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Lambertian Reflectance and Linear Subspaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Incremental Singular Value Decomposition of Uncertain Data with Missing Values
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Face Identification by Fitting a 3D Morphable Model Using Linear Shape and Texture Error Functions
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Fisher Light-Fields for Face Recognition across Pose and Illumination
Proceedings of the 24th DAGM Symposium on Pattern Recognition
SFS Based View Synthesis for Robust Face Recognition
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
The CMU Pose, Illumination, and Expression (PIE) Database
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rank Constrained Recognition under Unknown Illuminations
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Face Recognition in the Presence of Multiple Illumination Sources
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Separating Style and Content with Bilinear Models
Neural Computation
Journal of Cognitive Neuroscience
Face recognition under variable lighting using harmonic image exemplars
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Identifying faces across variations in lighting: Psychophysics and computation
ACM Transactions on Applied Perception (TAP)
Pose-encoded spherical harmonics for face recognition and synthesis using a single image
EURASIP Journal on Advances in Signal Processing
A methodology for rapid illumination-invariant face recognition using image processing filters
Computer Vision and Image Understanding
Face recognition across pose: A review
Pattern Recognition
Facial Reconstruction and Alignment Using Photometric Stereo and Surface Fitting
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
3D face reconstructions from photometric stereo using near infrared and visible light
Computer Vision and Image Understanding
Signature extraction using mutual interdependencies
Pattern Recognition
Face recognition in 2D and 2.5D using ridgelets and photometric stereo
Pattern Recognition
Remote identification of faces: Problems, prospects, and progress
Pattern Recognition Letters
SVDD-based illumination compensation for face recognition
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Separability oriented preprocessing for illumination-insensitive face recognition
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
Evaluating the effect of diffuse light on photometric stereo reconstruction
Machine Vision and Applications
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Traditional photometric stereo algorithms employ a Lambertian reflectance model with a varying albedo field and involve the appearance of only one object. In this paper, we generalize photometric stereo algorithms to handle all appearances of all objects in a class, in particular the human face class, by making use of the linear Lambertian property. A linear Lambertian object is one which is linearly spanned by a set of basis objects and has a Lambertian surface. The linear property leads to a rank constraint and, consequently, a factorization of an observation matrix that consists of exemplar images of different objects (e.g., faces of different subjects) under different, unknown illuminations. Integrability and symmetry constraints are used to fully recover the subspace bases using a novel linearized algorithm that takes the varying albedo field into account. The effectiveness of the linear Lambertian property is further investigated by using it for the problem of illumination-invariant face recognition using just one image. Attached shadows are incorporated in the model by a careful treatment of the inherent nonlinearity in Lambert's law. This enables us to extend our algorithm to perform face recognition in the presence of multiple illumination sources. Experimental results using standard data sets are presented.