Age estimation using active appearance models and ensemble of classifiers with dissimilarity-based classification

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6838 LNCS, Issue , 2011, Pages 327-334

  Kohli, Sharad ^a   Prakash, Surya ^a   Gupta, Phalguni ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY KANPUR   (India)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE APPEARANCE MODELS; AGE ESTIMATION; ENSEMBLE OF CLASSIFIERS; FACE IMAGES; MISCLASSIFICATION ERROR; NOVEL TECHNIQUES;

ARTIFICIAL INTELLIGENCE;

INTELLIGENT COMPUTING;

EID: 84857266079     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-24728-6_44     Document Type: Conference Paper

References (22)

1. Lanitis, A., Taylor, C.J., Cootes, T.F.: Toward automatic simulation of aging effects on face images. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(4), 442-455 (2002)
2. Chellappa, R.,Wilson, C.L., Sirohey, S.: Human and machine recognition of faces: a survey. Proceedings of the IEEE 83(5), 705-741 (1995)
3. Fasel, B., Luettin, J.: Automatic facial expression analysis: a survey. Pattern Recognition 36(1), 259-275 (2003)
4. O'toole, A.J., Deffenbacher, K.A., Valentin, D., Mckee, K., Huff, D., Abdi, H.: The Perception of Face Gender: The Role of Stimulus Structure in Recognition and Classification. Memory and Cognition 26, 146-160 (1997)
5. Albert, M., Ricanek, K., Patterson, E.: A review of the literature on the aging adult skull and face: Implications for forensic science research and applications. Forensic Science International 172(1), 1-9 (2007)
6. Magnus, C., Forsberg: Facial morphology and ageing: a longitudinal cephalometric investigation of young adults. European Journal of Orthodontics 1(1), 15-23 (1979)
7. Luu, K., Ricanek, K., Bui, T.D., Suen, C.Y.: Age estimation using active appearance models and support vector machine regression. In: Proceedings of the 3rd IEEE International Conference on Biometrics: Theory, Applications and systems, pp. 314-318 (2010)
8. Edwards, G.J., Lanitis, A., Taylor, C.J., Cootes, T.F.: Statistical models of face images -improving specificity. Image and Vision Computing 16(3), 203-211 (1998)
9. Ramanathan, N., Chellappa, R.: Face Verification across Age Progression. In: Proceeding of IEEE Conference of Computer Vision and Pattern Recognition, pp. 462-469 (2005)
10. Fu, Y., Huang, T.S.: Human Age EstimationWith Regression on Discriminative Aging Manifold. IEEE Transactions on Multimedia 10(4), 578-584 (2008)
11. Kwon, Y.H., da Vitoria Lobo, N.: Age Classification from Facial Images. Computer Vision and Image Understanding 74(1), 1-21 (1999)
12. Geng, X., Zhou, Z.-H., Zhang, Y., Li, G., Dai, H.: Learning from facial aging patterns for automatic age estimation. ACM Multimedia, 307-316 (2006)
13. Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active Appearance Models. IEEE Transactions on Pattern Analysis and Machine Intelligence 23(6), 681-685 (2001)
14. Kang, H., Cootes, T.F., Taylor, C.J.: A Comparison of Face Verification Algorithms using Appearance Models. In: British Machine Vision Conference, vol. 2, pp. 477-486 (2002)
15. Tang, F., Deng, B.: Facial Expression Recognition using AAM and Local Facial Features. In: Proceedings of the Third International Conference on Natural Computation ICNC 2007, vol. 02, pp. 632-635 (2007)
16. Kuncheva, L.I., Whitaker, C.J.: Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Accuracy. Machine Learning 51(2), 181-207 (2003)
17. Pekalska, E., Paclík, P., Duin, R.P.W.:A Generalized Kernel Approach to Dissimilarity-based Classification. Journal of Machine Learning Research 2, 175-211 (2001)
18. Blanco, Á ., Martín-Merino, M., De Las Rivas, J.: Ensemble of Support Vector Machines to Improve the Cancer Class Prediction Based on the Gene Expression Profiles. Innovations in Hybrid Intelligent Systems 44, 393-400 (2008)
19. Chen, Chun-houh, Wolfgang, Unwin, A., Cox, M.A.A., Cox, T.F.:Multidimensional Scaling Handbook of Data Visualization, pp. 315-347 (2008)
20. The FG-NET Aging Database, http://www.fgnet.rsunit.com/
21. Smola, A.J., Scholkopf, B.: A tutorial on support vector regression Statistics and Computing, vol. 14(3), pp. 199-222 (2004)
22. Wold, S., Eriksson, L., Kettaneh, N.: PLS in Data Mining and Data Integration. Handbook of Partial Least Squares, pp. 327-357 (2010)