Facial gender classification using shape-from-shading

Image and Vision Computing

Volumn 28, Issue 6, 2010, Pages 1039-1048

  Wu, Jing ^a   Smith, William A P ^a   Hancock, Edwin R ^a  

^a UNIVERSITY OF YORK   (United Kingdom)

Author keywords

Gender classification; Principal geodesic analysis; Shape from shading

Indexed keywords

DIFFERENTIAL AMPLIFIERS; FACE RECOGNITION; GEODESY; PROGRAMMED CONTROL SYSTEMS;

FACIAL SHAPE; FACIAL SHAPE INFORMATION; FACIAL SURFACES; GENDER CLASSIFICATION; HARD CONSTRAINTS; IMAGE INTENSITIES; INTENSITY IMAGES; PRINCIPAL GEODESIC ANALYSIS; SHAPE FROM SHADING; STATISTICAL MODELS;

NEEDLES;

EID: 77649337313     PISSN: 02628856     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.imavis.2009.09.003     Document Type: Article

References (47)

1. R. Brunelli, T. Poggio: HyberBF Networks for Gender Classification. In Proc. DARPA Image Understanding Workshop, 1992, pp.311-314.
2. M.K. Fleming, G.W. Cottrell: Categorization of faces using unsupervised feature extraction. 1990 IJCNN, vol.2, pages:65-70.
3. Golomb B., Lawrence D., and Sejnowski T. SexNet: A Neural Network Identifies Sex from Human Faces. Advances in Neural Information Processing Systems (1991) 572-577
4. Gutta S., Huang J.R.J., Jonathon P., and Wechsler H. Mixture of experts for classification of gender, ethnic origin, and pose of human faces. IEEE Trans Neural Networks 11 4 (2000) 948-960
5. Moghaddam B., and Yang M.H. Learning gender with support faces. IEEE Transaction Pattern Analysis and Machine Intelligence 24 5 (2002) 707-711
6. Kim H., Kim D., Ghahramani Z., and Bang S.Y. Appearance-based gender classification with Gaussian processes. Pattern Recognition Letters 27 6 (2006) 618-626
7. G. Shakhnarovich, P. Viola, and B. Moghaddam: A Unified Learning Framework for Real Time Face Detection and Classification. IEEE Int'l Conf. Automatic Face and Gesture Recognition, pp. 14-21, 2002.
8. B. Wu, H. Ai, and C. Huang: LUT-Based Adaboost for Gender Classification. Int'l Conf. Audio-and Video-Based Biometric Person Authentication, pp.104-110, 2003.
9. Jain A., and Huang J. Integrating Independent Components and Linear Discriminant Analysis for Gender Classification. FGR (2004) 159-163
10. Buchala S., Davey N., Gale T.M., and Frank R.J. Principal Component Analysis of Gender, Ethnicity, Age, and Identity of Face Images. Proc. IEEE ICMI (2005)
11. Sun Z., Bebis G., Yuan X., and Louis S.J. Genetic Feature Subset Selection for Gender Classification: A Comparison Study. WACV (2002) 165-170
12. Lu H., Huang Y., Chen Y., and Yang D. Automatic gender recognition based on pixel-pattern-based texture feature. J. Real-Time Image Processing 3 (2008) 109-116
13. T. Wilhelm, H.J. Bohme, and H.M. Gross: Classification of Face Images for Gender, Age, Facial Expression, and Identity, W.Duch et al. (Eds.): ICANN 2005, LNCS 3696, pp.569-574, 2005.
14. X. Lu, H. Chen, and A.K. Jain: Multimodal Facial Gender and Ethnicity Identification, Proc. International Conference on Biometrics (ICB), pp.554-561, HongKong, January, 2006.
15. Y. Saatci, C.P. Town: Cascaded Classification of Gender and Facial Expression using Active Appearance Models. Proc. International Conference on Automatic Face and Gesture Recognition, 2006.
16. Baluja S., and Rowley H. Boosting Sex Identification Performance. International Journal of Computer Vision 7 11 (2007) January
17. Burton A.M., Bruce V., and Dench N. What's the difference between men and women? Evidence from facial measurement. Perception 22 (1993) 153-176
18. Bruce V., Burton A.M., Hanna E., Healey P., Mason O., Coombes A., Fright R., and Linney A. Sex discrimination: how do we tell the difference between male and female faces?. Perception 22 (1993) 131-152
19. O'Toole A.J., Vetter T., Troje N.F., and Bulthoff H.H. Sex Classification is Better with Three-Dimensional Structure than with Image Intensity Information. Perception (1997) 130-136
20. Gosselin F., and Schyns P.G. Bubbles: a technique to reveal the use of information in recognition tasks. Vision Research 41 (2001) 2261-2271
21. T.F. Cootes, G.J. Edwards, and C.J. Taylor: Active Appearance Models. In Proc. European Conference on Computer Vision 1998, Vol.2, pp.484-498, Springer, 1998.
22. Zhang R., Tsai P.S., Cryer J.E., and Shah M. Shape-from-shading: a survey. IEEE Trans. PAMI 21 8 (1999) 690-706
23. E. Prados, O. Faugeras: A rigorous and realistic shape from shading method and some of its applications, INRIA, Tech. Rep. RR-5133, 2004.
24. M. Castelan, E.R. Hancock: Acquiring height maps of faces from a single image, in Proc. 3DPVT (2004) 183-190.
25. W.Y. Zhao, R. Chellappa: Illumination-intensitive face recognition using symmetric shape-from-shading, in Proc. CVPR, 2000.
26. Atick J.J., Griffin P.A., and Redlich A.N. Statistical approach to shape from shading: Reconstruction of 3D face surfaces from single 2D images. Neural Comp. 8 6 (1996) 1321-1340
27. Samaras D., and Metaxas D. Illumination constraints in deformable models for shape and light direction estimation. IEEE Trans. PAMI 25 2 (2003) 247-264
28. Smith W.A.P., and Hancock E.R. Facial Shape-from-shading and Recognition using Principal Geodesic Analysis and Robust Statistics. International Journal of Computer Vision 76 1 (2008) 71-91
29. Worthington P.L., and Hancock E.R. New constraints on data-closeness and needle map consistency for shape-from-shading. IEEE Trans. PAMI 21 12 (1999) 1250-1267 December
30. Fletcher P.T., Joshi S., Lu C., and Pizer S.M. Principal geodesic analysis for the study of nonlinear statistics of shape. IEEE Transactions on Medical Imaging 23 (2004) 995-1005
31. X. Pennec: Probabilities and statistics on riemannian manifolds: A geometric approach. Technical Report RR-5093, INRIA, 2004.
32. Sirovich L. Turbulence and the dynamics of coherent structures. Quart. Applied Mathematics XLV 3 (1987) 561-590
33. Fisher R.A. The use of Multiple Measures in Taxonomic Problems. Annals of Eugenics 7 (1936) 179-188
34. Belhumeur P.N., Hespanha J.P., and Kriegman D.J. Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection. IEEE Trans. PAMI 19 7 (1997) July
35. Flynn P.J., Bowyer K.W., and Phillips P.J. Assessment of time dependency in face recognition: An initial study. Audioand Video-Based Biometric Person Authentication (2003) 44-51
36. K.Chang, K.W. Bowyer, and P.J. Flynn: Face recognition using 2D and 3D facial data, ACM Workshop on Multimodal User Authentication, pp.25-32, December 2003.
37. Bookstein F.L. Principal Warps: Thin-Plate Splines and the Decomposition of Deformations. IEEE Trans. PAMI 11 6 (1989) 567-585
38. Robles-Kelly A., and Hancock E.R. Estimating the surface radiance function from single images. Graphical Models 67 6 (2005) 18-548 November
39. Makinen E., and Raisamo R. An experimental comparison of gender classification methods. Pattern Recognition Letters 29 (2008) 1544-1556
40. Makinen E., and Raisamo R. Evaluation of Gender Classification Methods with Automatically Detected and Aligned Faces. IEEE Tran. Pattern Analysis and Machine Intelligence 30 3 (2008) March
41. Hadid A., and Pietikainen M. Combining appearance and motion for face and gender recognition from videos. Pattern Recognition 42 (2009) 2818-2827
42. J. Wu, W.A.P. Smith, and E.R. Hancock: Gender Classification using Principal Geodesic Analysis and Gaussian Mixture Models. In Proc. CIARP, pages 58-67, 2006.
43. J. Wu, W.A.P. Smith, and E.R. Hancock: Weighted Principal Geodesic Analysis for Facial Gender Classification. In Proc. CIARP, pages 331-339, 2007.
44. J. Wu, W.A.P. Smith, and E.R.Hancock: Gender Classification Based on Facial Surface Normals. In Proc. ICPR, 2008.
45. X. Leng, Y. Wang: Improving Generalization for Gender Classification. In Proc. ICIP, pp. 1656-1659, 2008.
46. S.L. Phung and A. Bouzerdoum, Gender Classification Using a New Pyramidal Neural Network, International Conference on Neural Information Processing (2006) 207-216.
47. Phillips P.J., Moon H., Rauss P.J., and Rizvi S. The FERET evaluation methodology for face recognition algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 22 10 (2000) October