Cross-age reference coding for age-invariant face recognition and retrieval

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

Volumn 8694 LNCS, Issue PART 6, 2014, Pages 768-783

  Chen, Bor Chun ^a   Chen, Chu Song ^a   Hsu, Winston H ^b  

^a INSTITUTE OF INFORMATION SCIENCE   (Taiwan)

^b NATIONAL TAIWAN UNIVERSITY   (Taiwan)

Author keywords

Aging; Face Recognition

Indexed keywords

AGING OF MATERIALS; ENCODING (SYMBOLS);

CODING FRAMEWORK; COMPLEX MODEL; DATA-DRIVEN METHODS; IMAGE DATASETS; LARGE-SCALE DATASET; LINEAR PROJECTIONS; LOW-LEVEL FEATURES; STATE-OF-THE-ART PERFORMANCE;

FACE RECOGNITION;

EID: 84906331113     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-10599-4_49     Document Type: Conference Paper

References (40)

1. Ahonen, T., Hadid, A., Pietikainen, M.: Face description with local binary patterns: Application to face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 28(12), 2037-2041 (2006)
2. Barkan, O., Weill, J., Wolf, L., Aronowitz, H.: Fast high dimensional vector multiplication face recognition. In: Proc. IEEE Int'l Conf. Computer Vision (2013)
3. Berg, T., Belhumeur, P.N.: Tom-vs-pete classifiers and identity-preserving alignment for face verification. In: BMVC, vol. 1, p. 5 (2012)
4. Chen, D., Cao, X., Wen, F., Sun, J.: Blessing of dimensionality: High-dimensional feature and its efficient compression for face verification. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3025-3032. IEEE (2013)
5. Fan, R.E., Chang, K.W., Hsieh, C.J., Wang, X.R., Lin, C.J.: Liblinear: A library for large linear classification. The Journal of Machine Learning Research 9, 1871-1874 (2008)
6. Fu, Y., Huang, T.S.: Human age estimation with regression on discriminative aging manifold. IEEE Transactions on Multimedia 10(4), 578-584 (2008)
7. Geng, X., Zhou, Z.H., Smith-Miles, K.: Automatic age estimation based on facial aging patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(12), 2234-2240 (2007)
8. Gong, D., Li, Z., Lin, D., Liu, J., Tang, X.: Hidden factor analysis for age invariant face recognition. In: 2013 IEEE 14th International Conference on Computer Vision. IEEE (2013)
9. Gross, R., Matthews, I., Cohn, J., Kanade, T., Baker, S.: Multi-pie. Image and Vision Computing 28(5), 807-813 (2010)
10. Guo, G., Fu, Y., Dyer, C.R., Huang, T.S.: Image-based human age estimation by manifold learning and locally adjusted robust regression. IEEE Transactions on Image Processing 17(7), 1178-1188 (2008)
11. Huang, G.B., Ramesh, M., Berg, T., Learned-Miller, E.: Labeled faces in the wild: A database for studying face recognition in unconstrained environments. Tech. Rep. 07-49, University of Massachusetts, Amherst (October 2007)
12. Jain, A.K., Klare, B., Park, U.: Face matching and retrieval in forensics applications. IEEE MultiMedia 19(1), 20 (2012)
13. Kumar, N., Berg, A.C., Belhumeur, P.N., Nayar, S.K.: Attribute and simile classifiers for face verification. In: 2009 IEEE 12th International Conference on Computer Vision, pp. 365-372. IEEE (2009)
14. Kwon, Y.H., da Vitoria Lobo, N.: Age classification from facial images. In: Proceedings of the 1994 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1994, pp. 762-767. IEEE (1994)
15. Lanitis, A., Draganova, C., Christodoulou, C.: Comparing different classifiers for automatic age estimation. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 34(1), 621-628 (2004)
16. 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)
17. Li, Z., Park, U., Jain, A.K.: A discriminative model for age invariant face recognition. IEEE Transactions on Information Forensics and Security 6(3), 1028-1037 (2011)
18. Liao, Q., Leibo, J.Z., Mroueh, Y., Poggio, T.: Can a biologically- plausible hierarchy effectively replace face detection, alignment, and recognition pipelines? CoRR abs/1311.4082 (2013)
19. Ling, H., Soatto, S., Ramanathan, N., Jacobs, D.W.: Face verification across age progression using discriminative methods. IEEE Transactions on Information Forensics and Security 5(1), 82-91 (2010)
20. Face and Gesture Recognition Working group: FG-NET Aging Database (2000)
21. Montillo, A., Ling, H.: Age regression from faces using random forests. In: 2009 16th IEEE International Conference on Image Processing (ICIP), pp. 2465-2468. IEEE (2009)
22. Mu, G., Guo, G., Fu, Y., Huang, T.S.: Human age estimation using bio-inspired features. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009, pp. 112-119. IEEE (2009)
23. Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7), 971-987 (2002)
24. Park, U., Tong, Y., Jain, A.K.: Age-invariant face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(5), 947-954 (2010)
25. Ramanathan, N., Chellappa, R.: Face verification across age progression. IEEE Transactions on Image Processing 15(11), 3349-3361 (2006)
26. Ricanek, K., Tesafaye, T.: Morph: A longitudinal image database of normal adult age-progression. In: 7th International Conference on Automatic Face and Gesture Recognition, FGR 2006, pp. 341-345. IEEE (2006)
27. Simonyan, K., Parkhi, O.M., Vedaldi, A., Zisserman, A.: Fisher vector faces in the wild. In: Proc. BMVC, vol. 1, p. 7 (2013)
28. Suo, J., Chen, X., Shan, S., Gao, W.: Learning long term face aging patterns from partially dense aging databases. In: 2009 IEEE 12th International Conference on Computer Vision, pp. 622-629. IEEE (2009)
29. Suo, J., Zhu, S.C., Shan, S., Chen, X.: A compositional and dynamic model for face aging. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(3), 385-401 (2010)
30. Tsumura, N., Ojima, N., Sato, K., Shiraishi, M., Shimizu, H., Nabeshima, H., Akazaki, S., Hori, K., Miyake, Y.: Image-based skin color and texture analysis/synthesis by extracting hemoglobin and melanin information in the skin. ACM Transactions on Graphics (TOG) 22, 770-779 (2003)
31. Turk, M.A., Pentland, A.P.: Face recognition using eigenfaces. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1991, pp. 586-591. IEEE (1991)
32. Viola, P., Jones, M.J.: Robust real-time face detection. International Journal of Computer Vision 57(2), 137-154 (2004)
33. Wang, D., Hoi, S.C., He, Y., Zhu, J.: Retrieval-based face annotation by weak label regularized local coordinate coding. In: Proceedings of the 19th ACM International Conference on Multimedia, pp. 353-362. ACM (2011)
34. Wang, J., Shang, Y., Su, G., Lin, X.: Age simulation for face recognition. In: 18th International Conference on Pattern Recognition, ICPR 2006, vol. 3, pp. 913-916. IEEE (2006)
35. Wright, J., Yang, A.Y., Ganesh, A., Sastry, S.S., Ma, Y.: Robust face recognition via sparse representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 31(2), 210-227 (2009)
36. Wu, Z., Ke, Q., Sun, J., Shum, H.Y.: Scalable face image retrieval with identity-based quantization and multireference reranking. IEEE Transactions on Pattern Analysis and Machine Intelligence 33(10), 1991-2001 (2011)
37. Xiong, X., De la Torre, F.: Supervised descent method and its applications to face alignment. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 532-539. IEEE (2013)
38. Yan, S., Wang, H., Tang, X., Huang, T.S.: Learning auto-structured regressor from uncertain nonnegative labels. In: IEEE 11th International Conference on Computer Vision, ICCV 2007, pp. 1-8. IEEE (2007)
39. Yin, Q., Tang, X., Sun, J.: An associate-predict model for face recognition. In: 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 497-504. IEEE (2011)
40. Zhou, S.K., Georgescu, B., Zhou, X.S., Comaniciu, D.: Image based regression using boosting method. In: Tenth IEEE International Conference on Computer Vision, ICCV 2005, vol. 1, pp. 541-548. IEEE (2005)