A Method for Enforcing Integrability in Shape from Shading Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
Lambertian Reflectance and Linear Subspaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shapelets Correlated with Surface Normals Produce Surfaces
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Non-Lambertian Reflectance Modeling and Shape Recovery of Faces Using Tensor Splines
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D Face Reconstruction from a Single Image Using a Single Reference Face Shape
IEEE Transactions on Pattern Analysis and Machine Intelligence
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It has been known that it is hard to capture the high-frequency components (shadows and specularities) during the modeling of illumination effects. In this paper, we propose a reflectance model to simulate the interaction of light and the facial surface under the assumption that face is strictly axial symmetry. This model works well not only in fitting the intensities of pixel but also in processing the DC component contained in the image. To compute a facial 3D shape, we first augment the input images to get a symmetric facial normal field, then propose a method to obtain a more accurate normal field, and finally compute an integrable shape using the field. Experimental results for face relighting, facial shape recovery demonstrate the effectiveness of our method.