Facial Ethnic Appearance Synthesis
Abstract
In this work, we have explored several subspace reconstruction methods for facial ethnic appearance synthesis (FEAS). In our experiments, our proposed dual subspace modeling using the Fukunaga Koontz transform (FKT) yields much better facial ethnic synthesis results than the \(\ell _1\) minimization, the \(\ell _2\) minimization and the principal component analysis (PCA) reconstruction method. With that, we are able to automatically and efficiently synthesize different facial ethnic appearance and alter the facial ethnic appearance of the query image to any other ethnic appearance as desired. Our technique well preserves the facial structure of the query image and simultaneously synthesize the skin tone and ethnic features that best matches target ethnicity group. Facial ethnic appearance synthesis can be applied to synthesizing facial images of a particular ethnicity group for unbalanced database, and can be used to train ethnicity invariant classifiers by generating multiple ethnic appearances of the same subject in the training stage.
Keywords
Soft biometrics Ethnicity Face synthesis Fukunaga Koontz transformReferences
- 1.Dhamecha, T.I., Sankaran, A., Singh, R., Vatsa, M.: Is gender classification across ethnicity feasible using discriminant functions? In: 2011 International Joint Conference on Biometrics (IJCB), pp. 1–7 (September 2011)Google Scholar
- 2.Ekanadham, C., Tranchina, D., Simoncelli, E.P.: Recovery of sparse translation-invariant signals with continuous basis pursuit. IEEE Transactions on Signal Processing 59(10), 4735–4744 (2011)CrossRefMathSciNetGoogle Scholar
- 3.Fukunaga, K., Koontz, W.L.G.: Application of the karhunen-loève expansion to feature selection and ordering. IEEE Transactions on Computers C-19(4), 311–318 (1970)Google Scholar
- 4.Gill, P.R., Wang, A., Molnar, A.: The in-crowd algorithm for fast basis pursuit denoising. IEEE Transactions on Signal Processing 59(10), 4595–4605 (2011)CrossRefMathSciNetGoogle Scholar
- 5.Guo, G., Mu, G.: A study of large-scale ethnicity estimation with gender and age variations. In: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshop (CVPRW), pp. 79–86 (June 2010)Google Scholar
- 6.Hoang, T.V., Smith, E.H.B., Tabbone, S.: Edge noise removal in bilevel graphical document images using sparse representation. In: 2011 18th IEEE International Conference on Image Processing (ICIP), pp. 3549–3552 (September 2011)Google Scholar
- 7.Hosoi, S., Takikawa, E., Kawade, M.: Ethnicity estimation with facial images. In: Sixth IEEE International Conference on Automatic Face and Gesture Recognition (FG), pp. 195–200 (May 2004)Google Scholar
- 8.Jain, A.K., Park, U.: Facial marks: Soft biometric for face recognition. In: 2009 16th IEEE International Conference on Image Processing (ICIP), pp. 37–40 (November 2009)Google Scholar
- 9.Juefei-Xu, F., Bhagavatula, C., Jaech, A., Prasad, U., Savvides, M.: Gait-id on the move: pace independent human identification using cell phone accelerometer dynamics. In: 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS), pp. 8–15. IEEE (2012)Google Scholar
- 10.Juefei-Xu, F., Cha, M., Heyman, J.L., Venugopalan, S., Abiantun, R., Savvides, M.: Robust local binary pattern feature sets for periocular biometric identification. In: 2010 Fourth IEEE International Conference on Biometrics: Theory Applications and Systems (BTAS), pp. 1–8. IEEE (2010)Google Scholar
- 11.Juefei-Xu, F., Cha, M., Savvides, M., Bedros, S., Trojanova, J.: Robust periocular biometric recognition using multi-level fusion of various local feature extraction techniques. In: IEEE 17th International Conference on Digital Signal Processing (DSP) (2011)Google Scholar
- 12.Juefei-Xu, F., Luu, K., Savvides, M., Bui, T.D., Suen, C.Y.: Investigating age invariant face recognition based on periocular biometrics. In: 2011 International Joint Conference on Biometrics (IJCB), pp. 1–7. IEEE (2011)Google Scholar
- 13.Juefei-Xu, F., Pal, D.K., Savvides, M.: Hallucinating the full face from the periocular region via dimensionally weighted K-SVD. In: IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW). IEEE (2014)Google Scholar
- 14.Juefei-Xu, F., Savvides, M.: Can your eyebrows tell me who you are? In: 2011 5th International Conference on Signal Processing and Communication Systems (ICSPCS), pp. 1–8. IEEE (2011)Google Scholar
- 15.Juefei-Xu, F., Savvides, M.: Unconstrained periocular biometric acquisition and recognition using COTS PTZ camera for uncooperative and non-cooperative subjects. In: 2012 IEEE Workshop on Applications of Computer Vision (WACV), pp. 201–208. IEEE (2012)Google Scholar
- 16.Juefei-Xu, F., Savvides, M.: An augmented linear discriminant analysis approach for identifying identical twins with the aid of facial asymmetry features. In: IEEE Conference on Computer Vision and Pattern Recognition Workshop (CVPRW) (2013)Google Scholar
- 17.Juefei-Xu, F., Savvides, M.: An image statistics approach towards efficient and robust refinement for landmarks on facial boundary. In: 2013 IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS), pp. 1–8. IEEE (2013)Google Scholar
- 18.Juefei-Xu, F., Savvides, M.: Subspace based discrete transform encoded local binary patterns representations for robust periocular matching on NIST’s face recognition grand challenge. IEEE Transactions on Image Processing 23(8), 3490–3505 (2014)CrossRefMathSciNetGoogle Scholar
- 19.Juefei-Xu, F., Savvides, M.: Weight-optimal local binary patterns. In: European Conference on Computer Vision (ECCV) Workshops. Springer (2014)Google Scholar
- 20.Kashyap, A.L., Tulyakov, S., Govindaraju, V.: Facial behavior as a soft biometric. In: 2012 5th IAPR International Conference on Biometrics (ICB), pp. 147–151 (April 2012)Google Scholar
- 21.Li, Y., Savvides, M.: Kernel fukunaga-koontz transform subspaces for enhanced face recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2007, pp. 1–8 (June 2007)Google Scholar
- 22.Liu, C., Zakharov, Y.V., Chen, T.: Broadband underwater localization of multiple sources using basis pursuit de-noising. IEEE Transactions on Signal Processing 60(4), 1708–1717 (2012)CrossRefMathSciNetGoogle Scholar
- 23.Lu, W., Vaswani, N.: Modified basis pursuit denoising (modified-BPDN) for noisy compressive sensing with partially known support. In: 2010 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp. 3926–3929 (March 2010)Google Scholar
- 24.Lu, W., Vaswani, N.: Exact reconstruction conditions for regularized modified basis pursuit. IEEE Transactions on Signal Processing 60(5), 2634–2640 (2012)CrossRefMathSciNetGoogle Scholar
- 25.Lyle, J.R., Miller, P.E., Pundlik, S.J., Woodard, D.L.: Soft biometric classification using periocular region features. In: 2010 Fourth IEEE International Conference on Biometrics: Theory Application and Systems (BTAS), pp. 1–7 (September 2010)Google Scholar
- 26.Manesh, F.S., Ghahramani, M., Tan, Y.P.: Facial part displacement effect on template-based gender and ethnicity classification. In: 2010 11th International Conference on Control Automation Robotics and Vision (ICARCV), pp. 1644–1649 (December 2010)Google Scholar
- 27.Mota, J.F.C., Xavier, J.M.F., Aguiar, P.M.Q., Puschel, M.: Distributed basis pursuit. IEEE Transactions on Signal Processing 60(4), 1942–1956 (2012)Google Scholar
- 28.Niinuma, K., Park, U., Jain, A.K.: Soft biometric traits for continuous user authentication. IEEE Transactions on Information Forensics and Security 5(4), 771–780 (2010)Google Scholar
- 29.Park, U., Jain, A.K.: Face matching and retrieval using soft biometrics. IEEE Transactions on Information Forensics and Security 5(3), 406–415 (2010)Google Scholar
- 30.Reid, D.A., Nixon, M.S.: Using comparative human descriptions for soft biometrics. In: 2011 International Joint Conference on Biometrics (IJCB), pp. 1–6 (October 2011)Google Scholar
- 31.Savvides, M., Juefei-Xu, F.: Image matching using subspace-based discrete transform encoded local binary patterns (September 2013). http://www.google.com/patents/US20140212044
- 32.Seshadri, K., Savvides, M.: An analysis of the sensitivity of active shape models to initialization when applied to automatic facial landmarking. IEEE Transactions on Information Forensics and Security 7(4), 1255–1269 (2012)CrossRefGoogle Scholar
- 33.Wu, B., Ai, H., Huang, C.: Facial image retrieval based on demographic classification. In: 17th International Conference on Pattern Recognition (ICPR), vol. 3, pp. 914–917 (August 2004)Google Scholar
- 34.Yan, S., Wang, H., Tang, X., Liu, J., Huang, T.S.: Regression from uncertain labels and its applications to soft biometrics. IEEE Trans. on Information Forensics and Security 3(4), 698–708 (2008)Google Scholar
- 35.Zhang, G., Wang, Y.: Multimodal 2D and 3D facial ethnicity classification. In: 2009 Fifth International Conference on Image and Graphics (ICIG), pp. 928–932 (September 2009)Google Scholar