A Method for Enforcing Integrability in Shape from Shading Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Height and gradient from shading
International Journal of Computer Vision
Estimation of Illuminant Direction, Albedo, and Shape from Shading
IEEE Transactions on Pattern Analysis and Machine Intelligence
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Symmetric Shape-from-Shading Using Self-ratio Image
International Journal of Computer Vision
Lambertian Reflectance and Linear Subspaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multilinear Analysis of Image Ensembles: TensorFaces
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Extraction Based on ICA for Binary Classification Problems
IEEE Transactions on Knowledge and Data Engineering
Overview of the Face Recognition Grand Challenge
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Shape from Shading: A Well-Posed Problem?
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D and Infrared Face Reconstruction from RGB data using Canonical Correlation Analysis
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Recovering Facial Shape Using a Statistical Model of Surface Normal Direction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Estimation of Albedo for Illumination-Invariant Matching and Shape Recovery
IEEE Transactions on Pattern Analysis and Machine Intelligence
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Efficient 3D reconstruction for face recognition
Pattern Recognition
Surface-from-Gradients without Discrete Integrability Enforcement: A Gaussian Kernel Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic 3D reconstruction for face recognition
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Adaptive Noise Smoothing Filter for Images with Signal-Dependent Noise
IEEE Transactions on Pattern Analysis and Machine Intelligence
Molding face shapes by example
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Shape from recognition: a novel approach for 3-D face shape recovery
IEEE Transactions on Image Processing
Computer Vision and Image Understanding
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In this paper, we propose a fast 3-D facial shape recovery algorithm from a single image with general, unknown lighting. In order to derive the algorithm, we formulate a nonlinear least-square problem with two parameter vectors which are related to personal identity and light conditions. We then combine the spherical harmonics for the surface normals of a human face with tensor algebra and show that in a certain condition, the dimensionality of the least-square problem can be further reduced to one-tenth of the regular subspace-based model by using tensor decomposition (N-mode SVD), which greatly speeds up the computations. In order to enhance the shape recovery performance, we have incorporated prior information in updating the parameters. In the experiment, the proposed algorithm takes less than 0.4s to reconstruct a face and shows a significant performance improvement over other reported schemes.