Illuminating light field: image-based face recognition across illuminations and poses

We present an image-based method for face recognition across different illuminations and different poses, where the term 'image-based' means that only 2D images are used and no explicit 3D models are needed. As face recognition across illuminations and poses involves three factors, namely identity, illumination, and pose, generalizations from known identities to novel identities, from known illuminations to novel illuminations, and from known poses to unknown poses are desired. Our approach, called the illuminating light field, derives an identity signature that is invariant to illuminations and poses, where a subspace encoding is assumed for the identity, a Lambertain reflectance model for the illumination, and a light field model for the poses. Experimental results using the PIE database demonstrate the effectiveness of the proposed approach.

[1]  Azriel Rosenfeld,et al.  Face recognition: A literature survey , 2003, CSUR.

[2]  Terence Sim,et al.  The CMU Pose, Illumination, and Expression (PIE) database , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[3]  Ralph Gross,et al.  Fisher Light-Fields for Face Recognition across Pose and Illumination , 2002, DAGM-Symposium.

[4]  Amnon Shashua,et al.  On Photometric Issues in 3D Visual Recognition from a Single 2D Image , 2004, International Journal of Computer Vision.

[5]  David J. Kriegman,et al.  From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Ralph Gross,et al.  Eigen light-fields and face recognition across pose , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[7]  Ronen Basri,et al.  Lambertian Reflectance and Linear Subspaces , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Marc Levoy,et al.  Light field rendering , 1996, SIGGRAPH.

[9]  Joshua B. Tenenbaum,et al.  Learning bilinear models for two-factor problems in vision , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[10]  Alex Pentland,et al.  View-based and modular eigenspaces for face recognition , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[11]  Amnon Shashua,et al.  The Quotient Image: Class-Based Re-Rendering and Recognition with Varying Illuminations , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Sami Romdhani,et al.  Face Identification by Fitting a 3D Morphable Model Using Linear Shape and Texture Error Functions , 2002, ECCV.

[13]  Rama Chellappa,et al.  Rank constrained recognition under unknown illuminations , 2003, 2003 IEEE International SOI Conference. Proceedings (Cat. No.03CH37443).