Facial Shape Recovery from a Single Image with an Arbitrary Directional Light Using Linearly Independent Representation

Authors:
Minsik Lee;Chong-Ho Choi
Affiliations:
School of Electrical Engineering and Computer Science, Seoul National University, Seoul, Korea;School of Electrical Engineering and Computer Science, Seoul National University, Seoul, Korea
Venue:
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Year:
2009

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Abstract

By the assumption that a face image under an arbitrary point light source is a linear combination of three linearly independent random vectors , we propose a novel statistical Shape From Shading (SFS) algorithm which can recover 3-D facial shape irrespective of the illumination direction, unlike most other statistical SFS algorithms. The scaled surface normal vectors , which are the products of albedos and surface normal vectors, can be represented by three linearly independent random vectors if we assume that human face is Lambertian. Thanks to this linearly independent representation, 3-D facial shape reconstruction can be accomplished by a few matrix multiplication under an arbitrary point light source. The experimental results show that the proposed algorithm shows good performance under various light conditions at low computational cost.