What Is the Set of Images of an Object Under All Possible Illumination Conditions?
International Journal of Computer Vision
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
An efficient representation for irradiance environment maps
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Lambertian Reflectance and Linear Subspaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active Appearance Models Revisited
International Journal of Computer Vision
Towards an Illumination-Based 3D Active Appearance Model for Fast Face Alignment
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Efficient illumination independent appearance-based face tracking
Image and Vision Computing
Real-time combined 2D+3D active appearance models
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Face alignment under variable illumination
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Automatic face interpretation using fast 3D illumination-based AAM models
Computer Vision and Image Understanding
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We present a novel iterative approach for recovering 3D shape and albedo from face images affected by non-uniform lighting and non-frontal pose. We fit a 3D active appearance model based on illumination, to a novel face image. In contrast to other works where an initial pose is required, we only need a simple initialization in translation and scale. Our optimization method improves the Jacobian each iteration by using the parameters of lighting estimated in previous iterations. Our fitting algorithm obtains a compact set of parameters of albedo, 3D shape, 3D pose and illumination which describe the appearance of the input image. We show that our method is able to accurately estimate the parameters of 3D shape and albedo, which are strongly related to identity. Experimental results show that our proposed approach can be easily extended to face recognition under non-uniform illumination and pose variations.