Ethnicity- and Gender-based Subject Retrieval Using 3-D Face-Recognition Techniques

While the retrieval of datasets from human subjects based on demographic characteristics such as gender or race is an ability with wide-ranging application, it remains poorly-studied. In contrast, a large body of work exists in the field of biometrics which has a different goal: the recognition of human subjects. Due to this disparity of interest, existing methods for retrieval based on demographic attributes tend to lag behind the more well-studied algorithms designed purely for face matching. The question this raises is whether a face recognition system could be leveraged to solve these other problems and, if so, how effective it could be. In the current work, we explore the limits of such a system for gender and ethnicity identification given (1) a ground truth of demographically-labeled, textureless 3-D models of human faces and (2) a state-of-the-art face-recognition algorithm. Once trained, our system is capable of classifying the gender and ethnicity of any such model of interest. Experiments are conducted on 4007 facial meshes from the benchmark Face Recognition Grand Challenge v2 dataset.

[1]  Alexander M. Bronstein,et al.  Expression-Invariant Representations of Faces , 2007, IEEE Transactions on Image Processing.

[2]  Ioannis A. Kakadiaris,et al.  Three-Dimensional Face Recognition in the Presence of Facial Expressions: An Annotated Deformable Model Approach , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  L Tsogo,et al.  Multidimensional Scaling Methods for Many-Object Sets: A Review , 2000, Multivariate behavioral research.

[4]  Shumeet Baluja,et al.  Boosting Sex Identification Performance , 2005, International Journal of Computer Vision.

[5]  Ron Kimmel,et al.  Representation Analysis and Synthesis of Lip Images Using Dimensionality Reduction , 2006, International Journal of Computer Vision.

[6]  Alice J. O'Toole,et al.  The role of shape and texture information in sex classification , 1995 .

[7]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[8]  A. O'Toole,et al.  Sex Classification is Better with Three-Dimensional Head Structure Than with Image Intensity Information , 1997, Perception.

[9]  Ming-Hsuan Yang,et al.  Learning Gender with Support Faces , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Anil K. Jain,et al.  Ethnicity identification from face images , 2004, SPIE Defense + Commercial Sensing.

[11]  Edward H. Adelson,et al.  Shiftable multiscale transforms , 1992, IEEE Trans. Inf. Theory.

[12]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[13]  Haizhou Ai,et al.  Demographic Classification with Local Binary Patterns , 2007, ICB.

[14]  Patrick J. Flynn,et al.  Overview of the face recognition grand challenge , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[15]  Forrest W. Young.  Multidimensional Scaling: History, Theory, and Applications , 1987 .

[16]  Roope Raisamo,et al.  Evaluation of Gender Classification Methods with Automatically Detected and Aligned Faces , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[18]  Ron Kimmel,et al.  On Bending Invariant Signatures for Surfaces , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[19]  Alexander M. Bronstein,et al.  Efficient Computation of Isometry-Invariant Distances Between Surfaces , 2006, SIAM J. Sci. Comput..

[20]  Harry Wechsler,et al.  Mixture of experts for classification of gender, ethnic origin, and pose of human faces , 2000, IEEE Trans. Neural Networks Learn. Syst..

[21]  Edwin R. Hancock,et al.  Gender Classification using Shape from Shading , 2007, BMVC.

[22]  W. Härdle,et al.  Applied Multivariate Statistical Analysis , 2003 .

[23]  Edwin R. Hancock,et al.  Facial Gender Classification Using Shape from Shading and Weighted Principal Geodesic Analysis , 2008, ICIAR.

[24]  Bao-Liang Lu,et al.  Gender Recognition Using a Min-Max Modular Support Vector Machine , 2005, ICNC.

[25]  Anil K. Jain,et al.  Multimodal Facial Gender and Ethnicity Identification , 2006, ICB.

[26]  Gillian Rhodes,et al.  “Just another pretty face”: A multidimensional scaling approach to face attractiveness and variability , 2007, Psychonomic bulletin & review.

[27]  Masato Kawade,et al.  Ethnicity estimation with facial images , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..