Photometric method for determining surface orientation from multiple images
Shape from shading
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
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
Lambertian Reflectance and Linear Subspaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
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
Illumination Cones for Recognition under Variable Lighting: Faces
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient, Robust and Accurate Fitting of a 3D Morphable Model
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Active Appearance Models Revisited
International Journal of Computer Vision
Shapelets Correlated with Surface Normals Produce Surfaces
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
Pose-encoded spherical harmonics for face recognition and synthesis using a single image
EURASIP Journal on Advances in Signal Processing
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
Interpreting Face Images by Fitting a Fast Illumination-Based 3D Active Appearance Model
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
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
Generative face alignment through 2.5D active appearance models
Computer Vision and Image Understanding
| Hi-index | 0.00 |
We present an innovative and fast approach for face interpretation invariant to lighting and pose. Our approach performs interpretation by fitting a parametric 3D face model to an input image using an optimization algorithm. The parameters obtained after the fitting process describe the appearance of the face. The fitting process is automatic and only requires a 2D position and a scale factor as initialization. The proposed model is a natural 3D extension of active appearance models and is based on modeling, separately and simultaneously, 3D pose, 3D shape, albedo, and lighting. Our model is capable of synthesizing faces with arbitrary 3D shape, 3D pose, albedo and lighting. In order to fit the model to an input image, we propose a fast optimization algorithm able to fit face images with non-uniform lighting and arbitrary pose. Our algorithm, based on a gradient descent approach, executes a fast update to the Jacobian by using the lighting parameters estimated in each iteration of the fitting process. 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, suggest that our model can be extended to face recognition under non-uniform lighting and variable pose.