A study on human age estimation under facial expression changes

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2012, Pages 2547-2553

  Guo, Guodong ^a   Wang, Xiaolong ^a  

^a WEST VIRGINIA UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGE ESTIMATION; FACE IMAGES; FACIAL EXPRESSIONS; HUMAN AGE ESTIMATION; ROBUST METHODS; ROBUST SOLUTIONS; SYSTEMATIC STUDY;

COMPUTER VISION;

FACE RECOGNITION;

EID: 84866648927     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2012.6247972     Document Type: Conference Paper

References (24)

1. N. Ebner, M. Riediger, and U. Lindenberger. Faces - A database of facial expressions in young, middle-aged, and older women and men: Development and validation. Behavior Research Methods, 42(1):351-362, 2010.
2. FGNET. The fg-net aging database. In http://www.fgnet.rsunit.com/, 2002.
3. Y. Fu, G.-D. Guo, and T. S. Huang. Age synthesis and estimation via faces: A survey. IEEE Trans. Pattern Analysis and Machine Intelligence, 32(11):1955-1976, 2010.
4. G.-D. Guo, Y. Fu, C.Dyer, and T. S. Huang. Image-based human age estimation by manifold learning and locally adjusted robust regression. IEEE Trans. Image Processing, 17(7):1178-1188, 2008.
5. G.-D. Guo and G. Mu. Simultaneous dimensionality reduction and human age estimation via kernel partial least squares regression. In IEEE Conf. on Computer Vision and Pattern Recognition, pages 657-664, 2011.
6. G.-D. Guo, G. Mu, Y. Fu, C. Dyer, and T. S. Huang. A study on automatic age estimation on a large database. In IEEE International Conference on Computer Vision, pages 1986-1991, 2009.
7. G.-D. Guo, G. Mu, Y. Fu, and T. S. Huang. Human age estimation using bioinspired features. In IEEE Conference on Computer Vision and Pattern Recognition, pages 112-119, 2009.
8. D. Huang and F. D. la Torre. Bilinear kernel reduced rank regression for facial expression synthesis. In ECCV, 2010.
9. M. Minear and D. Park. A lifespan database of adult facial stimuli. Behavior Research Methods, Instruments, & Computers, 36(4):630-633, 2004.
10. B. Ni, Z. Song, and S. Yan. Web image mining towards universal age estimator. In ACM Multimedia, 2009.
11. N. Ramanathan, R. Chellappa, and S. Biswas. Age progression in human faces : A survey. Visual Languages and Computing, 2009.
12. K. Ricanek and T. Tesafaye. Morph: A longitudinal image database of normal adult age-progression. In IEEE Conf. on AFGR, pages 341-345, 2006.
13. R. Rosipal. Nonlinear partial least squares: An overview. In H. Lodhi and Y.Yamanishi, editors, Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques, pages 169-189. ACCM, IGI Global, 2011.
14. R. Rosipal and N. Kramer. Overview and recent advances in partial least squares. In C. Saunders, M. Grobelnik, S. Gunn, and J. Shawe-Taylor, editors, Subspace, Latent Structure and Feature Selection Techniques, pages 34-51. Springer, 2006.
15. W. Schwartz, H. Guo, and L. Davis. A robust and scalable approach to face identification. In ECCV, 2010.
16. W. Schwartz, A. Kembhavi, D. Harwood, and L. Davis. Human detection using partial least squares analysis. In ICCV, 2009.
17. T. Serre, L. Wolf, and T. Poggio. Object recognition with features inspired by visual cortex. In IEEE Conf. on Comput. Vision and Pattern Recognit., 2005.
18. A. Sharma and D. Jacobs. Bypassing synthesis: PLS for face recognition with pose, low-resolution and sketch. In CVPR, pages 593-600, 2011.
19. Z. Song, B. Ni, D. Guo, T. Sim, and S. Yan. Learning universal multi-view age estimator by video contexts. In ICCV, 2011.
20. V. N. Vapnik. Statistical Learning Theory. John Wiley, New York, 1998.
21. H. Wold. Path models with latent variables: The nipals approach. In H. M. Blalock and et al, editors, Quantitative Sociology: Internnational perspectives on mathematical and statistical model building, pages 307-357. Academic Press, 1975.
22. H.Wold. Partial least squares. In S. Kotz and N. Johnson, editors, Encyclopedia of Statistical Sciences, volume 6, pages 581-591. Wiley, New York, 1985.
23. S. Yan, D. Xu, B. Zhang, H. Zhang, Q. Yang, and S. Lin. Graph embedding and extensions: A general framework for dimensionality reduction. IEEE Trans. Pattern Anal. Mach. Intell., 29:40-51, 2007.
24. S. Yan, X. Zhou, M. Liu, M. Hasegawa-Johnson, and T. Huang. Regression from patch-kernel. In IEEE conf. on CVPR, 2008.