The impact of specular highlights on 3D-2D face recognition

One of the most popular form of biometrics is face recognition. Face recognition techniques typically assume that a face exhibits Lambertian reectance. However, a face often exhibits prominent specularities, especially in outdoor environments. These specular highlights can compromise an identity authentication. In this work, we analyze the impact of such highlights on a 3D-2D face recognition system. First, we investigate three different specularity removal methods as preprocessing steps for face recognition. Then, we explicitly model facial specularities within the face detection system with the Cook-Torrance reflectance model. In our experiments, specularity removal increases the recognition rate on an outdoor face database by about 5% at a false alarm rate of 10-3. The integration of the Cook-Torrance model further improves these results, increasing the verification rate by 19% at a FAR of 10-3.

[1]  Edwin R. Hancock,et al.  A probabilistic framework for specular shape-from-shading , 2002, Object recognition supported by user interaction for service robots.

[2]  Ioannis A. Kakadiaris,et al.  Bidirectional relighting for 3D-aided 2D face recognition , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[3]  Rama Chellappa,et al.  Robust Estimation of Albedo for Illumination-invariant Matching and Shape Recovery , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[4]  Athinodoros S. Georghiades,et al.  Incorporating the Torrance and Sparrow model of reflectance in uncalibrated photometric stereo , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[5]  Masato Tsukada,et al.  Specularity removal for enhancing face recognition , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[6]  Robert L. Cook,et al.  A Reflectance Model for Computer Graphics , 1987, TOGS.

[7]  David J. Kriegman,et al.  Specularity Removal in Images and Videos: A PDE Approach , 2006, ECCV.

[8]  Pawan Sinha,et al.  Face Recognition by Humans: Nineteen Results All Computer Vision Researchers Should Know About , 2006, Proceedings of the IEEE.

[9]  Anil K. Jain,et al.  Handbook of Face Recognition, 2nd Edition , 2011 .

[10]  Christian Riess,et al.  Illuminant color estimation for real-world mixed-illuminant scenes , 2011, 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops).

[11]  Lei Zhang,et al.  Face recognition from a single training image under arbitrary unknown lighting using spherical harmonics , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Steven A. Shafer,et al.  Using color to separate reflection components , 1985 .

[13]  Christophe Schlick,et al.  An Inexpensive BRDF Model for Physically‐based Rendering , 1994, Comput. Graph. Forum.

[14]  In-So Kweon,et al.  Fast Separation of Reflection Components using a Specularity-Invariant Image Representation , 2006, 2006 International Conference on Image Processing.

[15]  Katsushi Ikeuchi,et al.  Separating Reflection Components of Textured Surfaces Using a Single Image , 2005, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Narendra Ahuja,et al.  Real-Time Specular Highlight Removal Using Bilateral Filtering , 2010, ECCV.

[17]  K. Torrance,et al.  Theory for off-specular reflection from roughened surfaces , 1967 .

[18]  Dmitry Chetverikov,et al.  A Survey of Specularity Removal Methods , 2011, Comput. Graph. Forum.

[19]  Csaba Kelemen,et al.  A Microfacet Based Coupled Specular-Matte BRDF Model with Importance Sampling , 2001, Eurographics.

[20]  Sharath Pankanti,et al.  The relation between the ROC curve and the CMC , 2005, Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AutoID'05).

[21]  T M Lehmann,et al.  Color line search for illuminant estimation in real-world scenes. , 2001, Journal of the Optical Society of America. A, Optics, image science, and vision.

[22]  Kevin W. Bowyer,et al.  Face recognition technology: security versus privacy , 2004, IEEE Technology and Society Magazine.

[23]  Gang Hua,et al.  Face Relighting from a Single Image under Arbitrary Unknown Lighting Conditions , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  Elli Angelopoulou,et al.  Beyond the neutral interface reflection assumption in illuminant color estimation , 2010, 2010 IEEE International Conference on Image Processing.

[25]  Zihan Zhou,et al.  Nearest-Subspace Patch Matching for face recognition under varying pose and illumination , 2008, 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition.