An improved biometrics technique based on metric learning approach

Neurocomputing

Volumn 97, Issue , 2012, Pages 44-51

  Ben, Xianye ^a   Meng, Weixiao ^b   Yan, Rui ^c   Wang, Kejun ^d  

^a SHANDONG UNIVERSITY   (China)

^b HARBIN INSTITUTE OF TECHNOLOGY   (China)

^c RENSSELAER POLYTECHNIC INSTITUTE   (United States)

^d HARBIN ENGINEERING UNIVERSITY   (China)

Author keywords

Different walking states; Face recognition; Gait recognition; Metric learning; Variant face pose

Indexed keywords

BIOMETRIC APPLICATIONS; CLASSIFICATION RATES; DIFFERENT WALKING STATES; EIGEN DECOMPOSITION; FACE DATABASE; FACE POSE; GAIT RECOGNITION; LOCAL INFORMATION; MANIFOLD STRUCTURES; METRIC LEARNING; RADIAL BASIS FUNCTIONS; TRANSFORMATION MATRICES;

FACE RECOGNITION; LINEAR TRANSFORMATIONS; RADIAL BASIS FUNCTION NETWORKS;

BIOMETRICS;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BIOMETRY; CLASSIFICATION ALGORITHM; CORRELATION ANALYSIS; DATA BASE; DISCRIMINANT ANALYSIS; KERNEL METHOD; METRIC SYSTEM; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; RADIAL BASED FUNCTION;

EID: 84865315606     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2012.06.022     Document Type: Article

References (44)

1. Delac K., Grgic M. A survey of biometric recognition methods, Proceedings Elmar 2004. 46th International Symposium on Electronics in Marine, 2004: 184-193.
2. Zhao Q., Zhang David, Zhang L., Luo N. High resolution partial fingerprint alignment using pore-valley descriptors. Pattern Recognit. 2010, 43(3):1050-1061.
3. Sanchez-Avila C., Sanchez-Reillo R. Two different approaches for iris recognition using Gabor filters and multiscale zero-crossing representation. Pattern Recognit. 2005, 38(2):231-240.
4. Yang W., Sun C., Zhang L. A multi-manifold discriminant analysis method for image feature extraction. Pattern Recognit. 2011, 44(8):1649-1657.
5. Liu Z., Yin Y., Wang H., Song S., Li Q. Finger vein recognition with manifold learning. J. Network Comput. Appl. 2010, 33(3):275-282.
6. Subramanya A., Seltzer M.L., Acero A. Automatic removal of typed keystrokes from speech signals. IEEE Signal Process Lett. 2007, 14(5):363-366.
7. Zongyi Liu Sarkar S. Improved gait recognition by gait dynamics normalization. IEEE Trans. Pattern Anal. Mach. Intell. 2006, 28(6):863-876.
8. Quek C., Zhou.R.W. Antiforgery: a novel pseudo-outer product based fuzzy neural network driven signature verification system. Pattern Recognit. Lett. 2002, 23(14):1795-1816.
9. Yampolskiy Roman V., Govindaraju Venu Behavioural biometrics: a survey and classification. Int. J. Biometrics 2008, 1(1):81-113.
10. Domeniconi C., Gunopulos D. Jing Peng. Large margin nearest neighbor classifiers. IEEE Trans. Neural Networks 2005, 16(4):899-909.
11. Duda R., Hart P., Stork D Pattern Classification 2000, Wiley.
12. Comon P. Independent component analysis, a new concept. Signal Process. 1994, 36(3):287-314P.
13. Tenenbaum J.B., de Silva V., Langford J.C. A global geometric framework for nonlinear dimensionality reduction. Science 2000, 260:2319-2323P.
14. Roweis S., Saul L. Nonlinear dimensionality reduction by locally linear embedding. Science 2000, 290:2323-2326P.
15. Belkin M., Niyogi P. Laplacian eigenmaps for dimensionality reduction and data representation. Neural Comput. 2003, 15(6):1373-1396P.
16. He X., Niyogi P. Locality preserving projections. Adv. Neural Inf. Process. Syst. 2004.
17. He X., Cai D., Yan S., Zhang H. Neighborhood preserving embedding. In Proc. ICCV 2005, 2:1208-1213P.
18. Yang J., Yang J. Why can LDA be performed in PCA transformed space. Pattern Recognit. 2003, 36(2):563-566P.
19. Sugiyama M. Local fisher discriminant analysis for supervised dimensionality reduction. In Proc. ICML 2006, 905-912P.
20. Ye J., Li T., Xiong T., Janardan R. Using uncorrelated discriminant analysis for tissue classification with gene expression data. IEEE/ACM Trans. Comput. Biol. Bioinf. 2004, 4(1):181-190P.
21. Ye J. Characterization of a family of algorithms for generalized discriminant analysis on undersampled problems. J. Mach. Learn. Res. 2005, 6(4):483-502P.
22. Noushath S., Kumar G.H., Shivakumar P. Diagonal Fisher linear discriminant analysis for efficient face recognition. Neurocomputing 2006, 69(13-15):1711-1716P.
23. Bobick A F, Davis JW. The recognition of human movement using temporal templates. IEEE Trans. PAMI 2001, 23(3):257-267P.
24. Chen Shi Gao Youxing. Gait recognition with wavelet moments of silhouette change images. J. Xi'an Jiaotong Univ. 2009, 43(1):90-94P.
25. Shi Chen, Tian-jun Ma, Wan-hong Huang, et al. A multi-layer windows method of moments for gait recognition. J. Electron. Inf. Technol. 2009, 31(1):116-119P.
26. Liu Jianyi, Zheng Nanning Gait history image: a novel temporal template for gait. IEEE Int. Conf. Recognit. Multimedia Expo 2007, 663-666P.
27. Lam T, Lee R.A New representation for human gait recognition: motion silhouette image MSI. Int. Conf. Biometrics 2006, 612-618P.
28. Yang J., Wu X., Peng Z. Gait recognition based on difference motion slice. Proc. 8th Int. Conf. Signal Process. 2006, 16-20P.
29. Han J, Bhanu B. Individual recognition using gait energy image. IEEE Trans Pattern Anal. Mach. Intell. 2006, 28(2):316-322P.
30. Yang Xiaochao, Zhou Yue, Zhang Tianhao, et al. Gait recognition based on dynamic region analysis. Signal Process. 2008, 88(9):2350-2356P.
31. Huang Guo Chang, Wang Yun-Hong Human gait recognition based on X-T plane energy images. Int. Conf. Wavelet Anal. Pattern Recognit. (ICWAPR'07 2007, 3:1134-1138P.
32. Bashir K, Xiang Tao, Gong Shaogang Gait recognition without subject cooperation. Pattern Recognit. Lett. 2010, 31(13):2052-2060P.
33. Toby HWL, Cheung KH, James NKL. Gait flow image: a silhouette-based gait representation for human identification. Pattern Recognit. 2011, 44(4):973-987P.
34. Bar-Hillel A., Hertz T., Shental N., Weinshall D. Learning distance functions using equivalence relations. In Proc. ICML 2003, 11-18P.
35. Jacob G., Sam R., Geoffrey H., Ruslan S. Neighbourhood components analysis. In Proc. NIPS 2005, 13-18P.
36. Weinberger K., Blitzer J., Saul L. Distance metric learning for large margin nearest neighbor classification. Adv. Neural Inf. Process. Syst. 2006, 18:1473-1480P.
37. Xiang S., Nie F., Zhang C. Learning a Mahalanobis distance metric for data clustering and classification. Pattern Recognit. 2008, 41(12):3600-3612P.
38. Wang M., Liu B., Tang J., Hua X. Metric learning with feature decomposition for image categorization. Neurocomputing 2010, 73(10-12):1562-1569P.
39. Yu S., Tan D., Tan T. A framework for evaluating the effect of view angle, clothing and carrying condition on gait recognition. Proc. 18th Int. Conf. Pattern Recognit. Hong Kong, China 2006, 441-444.
40. NATO ASI Series F 1998, Vol. 163:446-456.
41. Ben X.Y., Meng W.X., Yan R. Dual-ellipse fitting approach for robust gait periodicity detection. Neurocomputing 2012, 79:173-178. March.
42. Xianye BEN, Kejun WANG, Rui YAN, Oluwatoyin Pius.POPOOLA Subpattern-based complete two dimensional principal component analysis for gait recognition. Proc. China Assoc. Sci. Technol. 2011, 7:16-22.
43. Huang H, He H. Super-resolution method for face recognition using nonlinear mappings on coherent features. IEEE Trans. Neural Networks 2011, 22(1):121-130P.
44. Phillips P.J., Moon Hyeonjoon, Rizvi S.A., Rauss P.J. The FERET evaluation methodology for face-recognition algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 2000, 22(10):1090-1104P.