Recovering Facial Shape Using a Statistical Model of Surface Normal Direction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Facial gender classification using shape-from-shading
Image and Vision Computing
Approximating 3D facial shape from photographs using coupled statistical models
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
A coupled statistical model for face shape recovery
SSPR'06/SPR'06 Proceedings of the 2006 joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
Modelling surface normal distribution using the azimuthal equidistant projection
IMA'05 Proceedings of the 11th IMA international conference on Mathematics of Surfaces
Single image estimation of facial albedo maps
BVAI'05 Proceedings of the First international conference on Brain, Vision, and Artificial Intelligence
A model-based method for face shape recovery
IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I
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In this paper we explore how to improve the quality of the height map recovered from faces using shape-from-shading. One of the problems with reliable face surface reconstruction using shape-from-shading is that local errors in the needle map can cause implosion of facial features, and in particular the nose. To overcome this problem in this paper we develop a method for ensuring surface convexity. This is done by modifying the gradient orientations in accordance with critical points on the surface. We utilize a local shape indicator as a criteria to decide which surface normals are to be modified. Experiments show that altering the directions of a surface normal field of a face leads to a considerable improvement in its integrated height map.