基于标签敏感最大间隔准则的人脸年龄两步估计算法

doi:10.11896/j.issn.1002-137X.2018.06.050

Abstract

Abstract: Traditional maximum margin criterion usually ignores the differences between classes in the computation of the between-class scatter matrix.However,for facial age estimation,the differences between age labels are very significant.Therefore,this paper proposed a novel dimensionality reduction algorithm,called label-sensitive maximum margin criterion (lsMMC),by introducing a distance metric between the classes.In addition,considering the complicated facial aging process,this paper proposed a two-steps local regression algorithm named K nearest neighbors-label distribution support vector regressor (KNN-LDSVR) for age estimation.The mean absolute error of the proposed facial aging estimation method on the FGNET database subset is 4.1 years,which improves the performance compared with existing age estimation methods.

Key words: Age estimation, Label-sensitive, Local regression, Maximum margin criterion, Two-steps

CLC Number:

TP391.4

XU Xiao-ling, JIN Zhong, BEN Sheng-lan. Facial Age Two-steps Estimation Algorithm Based on Label-sensitive Maximum Margin Criterion[J].Computer Science, 2018, 45(6): 284-290.

References

[1]GUO G,MU G,FU Y,et al.Human age estimation using bio-inspired features[C]//IEEE International Conference on Compu-ter Vision and Pattern Recognition.2009:112-119.
[2]COOTES T F,EDWARDS G J,TAYLOR C J.Active appearance models[C]//European Conference on Computer Vision.1998:484-498.
[3]DONG Y,LIU Y,LIAN S.Automatic age estimation based on deep learning algorithm[J].Neurocomputing,2016,187:4-10.
[4]MA B,SHAN S,CHEN X,et al.Discriminant analysis for perceptionally comparable classes[C]//IEEE International Confe-rence on Automatic Face & Gesture Recognition.2008:1-6.
[5]CHAO W L,LIU J Z,DING J J.Facial age estimation based on label-sensitive learning and age-oriented regression[J].Pattern Recognition,2013,46(3):628-641.
[6]ONIFADE O F W,AKINYEMI D J.A review on the suitability of machine learning approaches to facial age estimation[J].International Journal of Modern Education and Computer Science,2015,7(12):17-28.
[7]PONTES J K,BRITTO A S,FOOKES C,et al.A flexible hierarchical approach for facial age estimation based on multiple features[J].Pattern Recognition,2016,54(C):34-51.
[8]GENG X,YIN C,ZHOU Z H.Facial age estimation by learning from label distributions[J].IEEE Transactions on Pattern Ana-lysis and Machine Intelligence,2013,35(10):2401-2412.
[9]HE Z,LI X,ZHANG Z,et al.Data-dependent label distribution learning for age estimation[J].IEEE Transactions on Image Processing,2017,26(8):3846-3858.
[10]The FG-NET Aging Database [OL].http://sting.cycollege.ac.cy/~lanitis/fgnetaging.
[11]LI H,JIANG T,ZHANG K.Efficient and robust feature extraction by maximum margin criterion[J].IEEE Transactions on Neural Networks,2006,17(1):157-165.
[12]MIKA S,RATSCH G,WESTON J,et al.Fisher discriminant analysis with kernels[C]//IEEE International Conference on Signal Processing.1999:41-48.
[13]SUGIYAMA M.Dimensionality reduction of multimodal labeled data by local fisher discriminant analysis[J].Journal of Machine Learning Research,2007,8(5):1027-1061.
[14]GENG X,HOU P.Pre-release prediction of crowd opinion on movies by label distribution learning[C]//International Joint Conference on Artificial Intelligence.2015:3511-3517.
[15]GOODALL C.Procrustes methods in the statistical analysis of shape[J].Journal of the Royal Statistical Society,1991,53(2):285-339.
[16]LANITIS A,TAYLOR C J,COOTES T F.Toward automatic simulation of aging effects on face images[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2002,24(4):442-455.
[17]GENG X,ZHOU Z H,ZHANG Y,et al.Learning from facial aging patterns for automatic age estimation[C]//ACM International Conference on Multimedia.2006:307-316.
[18]GENG X,ZHOU Z H,SMITH-MILES K.Automatic age estimation based on facial aging patterns[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2007,29(12):2234-2240.
[19]CHANG K Y,CHEN C S,HUNG Y P.A ranking approach for human ages estimation based on face images[C]//IEEE International Conference on Pattern Recognition.2010:3396-3399.
[20]CHOI S E,LEE Y J,LEE S J,et al.Age estimation using a hierarchical classifier based on global and local facial features[J].Pattern Recognition,2011,44(6):1262-1281.
[21]WU T,TURAGA P,CHELLAPPA R.Age estimation and face verification across aging using landmarks[J].IEEE Transactions on Information Forensics and Security,2012,7(6):1780-1788.
[22]LIU J,MA Y,DUAN L,et al.Hybrid constraint SVR for facial age estimation[J].Signal Processing,2014,94(1):576-582.
[23]SI J,FENG J,BU Q,et al.Age estimation based on canonical correlation analysis and extreme learning machine[C]//Chinese Conference on Biometric Recognition.2015:677-685.
[24]TIAN Q,XUE H,QIAO L.Human age estimation by considering both the ordinality and similarity of ages[J].Neural Processing Letters,2016,43(2):1-17.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

Facial Age Two-steps Estimation Algorithm Based on Label-sensitive Maximum Margin Criterion

PDF (PC)

Abstract

Cite this article

share this article

References

Related Articles 7

Metrics

Comments

Recommended 0

[1]	DU Liang, REN Xin, ZHANG Hai-ying, ZHOU Peng. Multiple Kernel Clustering via Local Regression Integration [J]. Computer Science, 2021, 48(8): 47-52.
[2]	SUN Jin-guang, RONG Wen-zhao. Research on Regional Age Estimation Model [J]. Computer Science, 2018, 45(8): 41-49.
[3]	ZHAO Chun-hui and CHEN Cai-kou. Modular Two-dimensional Locality Preserving Discriminant Analysis and its Application in Human Face Recognition [J]. Computer Science, 2015, 42(Z11): 142-145.
[4]	LIU Hui, WAN Ming-hua and WANG Qiao-li. Modular MMC and its Application in Face Recognition [J]. Computer Science, 2015, 42(8): 78-81.
[5]	LIN Shi-miao, MAO Xiao-jiao and YANG Yu-bin. Age Estimation Based on Facial Image [J]. Computer Science, 2015, 42(6): 32-36.
[6]	YUAN Min,YANG Rui-guo,YUAN Yuan and LEI Ying-ke. New Supervised Manifold Learning Method Based on MMC [J]. Computer Science, 2014, 41(4): 273-279.
[7]	JIANG Sheng-li, KUANG Chun-lin,ZHANG Jun-ying. Locality Preserving Discriminant Analysis Algorithm for Feature Extraction [J]. Computer Science, 2011, 38(4): 272-274.