Dense SIFT and Gabor descriptors-based face representation with applications to gender recognition

11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010

Volumn , Issue , 2010, Pages 1860-1864

  Wang, Jian Gang ^a   Li, Jun ^a   Lee, Chong Yee ^a   Yau, Wei Yun ^a  

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

Author keywords

AdaBoost; Dense SIFT; Fusion; Gabor; Gender recognition

Indexed keywords

ADABOOST; DENSE SIFT; FUSION; GABOR; GENDER RECOGNITION;

ADAPTIVE BOOSTING; COMPUTER VISION; FEATURE EXTRACTION; ROBOTICS;

FACE RECOGNITION;

EID: 79952364808     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICARCV.2010.5707370     Document Type: Conference Paper

References (38)

1. M. Bicego, A. Lagorio, E. Grosso, and M. Tistarelli, "On the use of SIFT features for face authentication," in Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop. IEEE Computer Society, 2006, p. 35.
2. B.A. Golomb, D.T Lawrence. and T.J. Sejnowski, "Sex-Net: a neural network identifies sex from human faces", in Proceedings of Advances in neural information processing systems, pp. 572-577, 1990.
3. G.W. Cottrell and J. Metcalfe, "EMATH: face, emotion, and gender recognition using holons", Proceedings of Advances in neural information processing systems, pp. 564-571, 1990.
4. R. Brunelli and T. Poggio, "HyperBF networks for gender classification", in Proceedings of the DARPA Image Understanding Workshop, pp. 311-314, 1992.
5. L. Wiskott, Fellous J.M., Kruger N. and Von der Malsburg C., "Face recognition and gender determination", in Proceedings on Automatic Face and Gesture Recognition, pp. 92-97, 1995.
6. S. Tamura, Kawai H. and Mitsumoto H., "Male/female identification from 8x6 very low resolution face images by neural network", in Pattern Recognition, 29(2) 331-335, February 1996. (Pubitemid 126397838)
7. Z Sun., Bebis G., Yuan X. and Louis S.J., "Genetic feature subset selection for gender classification: a comparison study", in IEEE Proceedings on Applications of Computer Vision, pp. 165-170, 2002.
8. S. Gutta, J.R.J. Huang, P. Jonathon and H. Wechsler, "Mixture of experts for classification of gender, ethnic origin, and pose of human faces", in IEEE Transactions on Neural Networks, 11(4) 948-960, July 2000.
9. M. Nakano, F. Yasukata and M. Fukumi, "Age and gender classification from face images using neural networks", Signal and Image Processing, 2004.
10. X. Lu, H. Chen and A.K. Jain, "Multimodal facial gender and ethnicity identification", Proceedings of Advances in Biometrics, vol. 3832/2005, pp.554- 561, December 2005.
11. B. Moghaddam and M.-H. Yang, "Gender classification with support vector machines", Proceedings of IEEE International Conference on Automatic Face and Gesture Recognition, pp. 306-311, March 2000.
12. Y. Saatci and C. Town, "Cascaded classification of gender and facial expression using active appearance models", Proceedings of International Conference on Automatic Face and Gesture Recognition, pp.393-398, April 2006.
13. H.-C. Kim, D. Kim, Z. Ghahramani and S.Y. Bang, "Appearance based gender classification with Gaussian processes", in Pattern Recognition Letters, 27(6) 618-626, April 2006. (Pubitemid 43254605)
14. Z. Yang, M. Li and H. Ai, "An Experimental Study on Automatic Face Gender Classification", Proceedings of IEEE International Conference on Pattern Recognition, pp.1099-1102, August 2006.
15. S. Baluja and H.A Rowley., "Boosting Sex Identification Performance", in International Journal of Computer Vision, vol. 71, iss. 1, pag. 111-119, January 2007. (Pubitemid 44343155)
16. C. Shan, S Gong and P. W. Mcowan, "Learning gender from human gaits and faces", in IEEE Proceedings on Advanced Video and Signal Based Surveillance, pag.505-510, September 2007.
17. T. Bfiri, F. Moutarde, N. Bourdis amd B. Steux, AdaBoost with "keypoint presence features for real-time vehicle visual detection, CoRR abs/0910.1273: (2009)
18. Z. Zhang, M. Li, K. Huang and T. Tan, Boosting local feature descriptors for automatic objects classification in traffic scene surveillance, , ICPR 2008: 1-4.
19. W. Zhang, B. Yu, G. J. Zelinsky and D. Samaras, Object class recognition using multiple layer boosting with heterogeneous features, , CVPR2005, Pages: 323-330
20. P. Dreuw, P. Steingrube H. Hanselmann, H. Ney SURF-Face: Face Recognition Under Viewpoint Consistency Constraints, BMVC2007.
21. th International Conference for Young Computer Scientist, pp. 1766-1770.
22. A. Albiol, D. Monzo, A. Martin, J. Sastre and A. Albiol, Face recognition using HOG-EBGM, PRL, (2008) 1537-1543.
23. P.-O. Ladoux, C. Rosenberger and B. Dorizzi, Palm Vein Verification System Based on SIFT Matching, ICB2009.
24. B. G. S, and P. Gupta, Palmprint based verification systems using SURF features, Second International Conference on Contemporary Computing, IC3 2009, Noida, India, August 17-19, 2009. Proceedings
25. L. Cao, M. Dikmen, Y. Fu and T. S. Huang Gender Recognition from Body, Proceeding of the 16th ACM international conference on Multimedia.
26. E. Tola, V. Lepetit, P. Fua. DAISY: An Efficient Dense Descriptor Applied to Wide-Baseline Stereo, IEEE Trans. on PAMI.
27. C. Liu, SIFT flow: dense correspondence across different scenes. In. ECCV, 2008
28. Y. Yuan, Y. Pang, X. Li, Footware for gender recognition, IEEE Transactions on Circuit and system for video technologies, 2010, 20(1): 131-135.
29. Lowe, D. G., "Distinctive Image Features from Scale-Invariant Keypoints", International Journal of Computer Vision, 60, 2, pp. 91-110, 2004.
30. N. Dalal and B. Triggs, Histograms of Oriented Gradients for Human Detection, CVPR2005.
31. H. Bay, A. Ess, T. Tuytelaars, L. V. Gool, "SURF: Speeded Up Robust Features", Computer Vision and Image Understanding (CVIU), Vol. 110, No. 3, pp. 346-359, 2008.
32. Yale face database, http://cvc.yale.edu/projects/yalefaces/yalefaces.html
33. S. Belongie, J. Malik and J. Puzicha, Shape matching and object recognition using shape contexts, PAMI, 24(4) 509-522, 2002. (Pubitemid 34448769)
34. W. Zhang, B. Yu, G. J. Zelinsky, D. Samaras, Object class recognition using multiple layer boosting with heterogeneous features, Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2, pp.323-330
35. OpenCV, http://sourceforge.net/projects/opencvlibrary/
36. D. Comaniciu, V. Ramesh, P. Meer, "kernel-based object tracking," PAMI, 25(5): 564-577, 2003.
37. A. Hadid and M. Pietikäinen, "Combining Motion and Appearance for Gender Classification from Video Sequences, Pattern Recognition", 42(11), 2009, pp: 2818-2827.
38. Y. Ke, R. Sukthankar, "PCA-SIFT: A More Distinctive Representation for Local Image Descriptors", CVPR 2004, II-506-II-513 Vol.2.