Advertisement

An ICA-Based Other-Race Effect Elimination for Facial Expression Recognition

  • Mingliang Xue
  • Xiaodong Duan
  • Wanquan Liu
  • Yuehai Wang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10996)

Abstract

Other-race effect affects the performance of multi-race facial expression recognition significantly. Though this phenomenon has been noticed by psychologists and computer vision researchers for decades, few work has been done to eliminate this influence caused by other-race effect. This work proposes an ICA-based other-race effect elimination method for 3D facial expression recognition. Firstly, the local depth features are extracted from 3D face point clouds, and then independent component analysis is used to project the features into a subspace in which the feature components are mutually independent. Second, a mutual information based feature selection method is adopted to determine race-sensitive features. Finally, the features after race-sensitive information elimination are utilized to conduct facial expression recognition. The proposed method is evaluated on BU-3DFE database, and the results reveal that the proposed method is effective to other-race effect elimination and could improve the multi-race facial expression recognition performance.

Keywords

Other-race effect Facial expression recognition Feature selection 

References

  1. 1.
    Malpass, R.S., Kravitz, J.: Recognition for faces of own and other race. J. Pers. Soc. Psychol. 13(4), 330 (1969)CrossRefGoogle Scholar
  2. 2.
    Fu, S., He, H., Hou, Z.G.: Learning race from face: a survey. IEEE Trans. Pattern Anal. Mach. Intell. 36(12), 2483–2509 (2014)CrossRefGoogle Scholar
  3. 3.
    Phillips, P.J., Jiang, F., Narvekar, A., Ayyad, J., O’Toole, A.J.: An other-race effect for face recognition algorithms. ACM Trans. Appl. Percept. (TAP) 8(2), 14 (2011)Google Scholar
  4. 4.
    Feingold, G.A.: The influence of environment on identification of persons and things. J. Am. Inst. Crim. Law Criminol. 5(1), 39–51 (1914)CrossRefGoogle Scholar
  5. 5.
    Dailey, M.N., Joyce, C., Lyons, M.J., Kamachi, M., Ishi, H., Gyoba, J., Cottrell, G.W.: Evidence and a computational explanation of cultural differences in facial expression recognition. Emotion 10(6), 874 (2010)CrossRefGoogle Scholar
  6. 6.
    Craig, B.M., Jing, Z., Lipp, O.V.: Facial race and sex cues have a comparable influence on emotion recognition in chinese and australian participants. Attention Percept. Psychophysics 1, 1–12 (2017)Google Scholar
  7. 7.
    Yan, X., Andrews, T.J., Jenkins, R., Young, A.W.: Cross-cultural differences and similarities underlying other-race effects for facial identity and expression. Q. J. Experimental Psychol. 69(7), 1247–1254 (2016)CrossRefGoogle Scholar
  8. 8.
    Zhen, Q., Huang, D., Wang, Y., Chen, L.: Muscular movement model based automatic 3D facial expression recognition. In: He, X., Luo, S., Tao, D., Xu, C., Yang, J., Hasan, M.A. (eds.) MMM 2015. LNCS, vol. 8935, pp. 522–533. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-14445-0_45CrossRefGoogle Scholar
  9. 9.
    Yin, L., Wei, X., Sun, Y., Wang, J., Rosato, M.J.: A 3D facial expression database for facial behavior research. In: 7th International Conference on Automatic Face and Gesture Recognition (FGR 2006), pp. 211–216. IEEE (2006)Google Scholar
  10. 10.
    Darwin, C., Rachman, I.J.: The Expression of Emotions in Man and Animals. Julian Friedmann (1979)Google Scholar
  11. 11.
    Ekman, P., Sorenson, E.R., Friesen, W.V.: Pan-cultural elements in facial displays of emotion. Science 164(3875), 86–88 (1969)CrossRefGoogle Scholar
  12. 12.
    Susskind, J.M., Lee, D.H., Cusi, A., Feiman, R., Grabski, W., Anderson, A.K.: Expressing fear enhances sensory acquisition. Nature Neurosci. 11(2), 843–850 (2008)CrossRefGoogle Scholar
  13. 13.
    Ekman, P., Friesen, W.V.: Facial action coding system (FACS): a technique for the measurement of facial actions. Rivista Di Psichiatria 47(2), 126–38 (1978)Google Scholar
  14. 14.
    Jack, R.E., Blais, C., Scheepers, C., Schyns, P.G., Caldara, R.: Cultural confusions show that facial expressions are not universal. Curr. Biol. 19(18), 1543–8 (2009)CrossRefGoogle Scholar
  15. 15.
    Jack, R.E., Garrod, O.G.B., Yu, H., Caldara, R., Schyns, P.G.: Facial expressions of emotion are not culturally universal. Proc. Nat. Acad. Sci. U.S.A. 109(19), 7241–7244 (2012)CrossRefGoogle Scholar
  16. 16.
    Natu, V., O’Toole, A.J.: Neural perspectives on the other-race effect. Vis. Cognit. 21(9–10), 1121–1137 (2013)Google Scholar
  17. 17.
    Xue, M., et al.: A computational other-race-effect analysis for 3D facial expression recognition. In: You, Z. (ed.) CCBR 2016. LNCS, vol. 9967, pp. 483–493. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-46654-5_53
  18. 18.
    Dailey, M.N., Cottrell, G.W., Padgett, C., Adolphs, R.: Empath: a neural network that categorizes facial expressions. J. Cognit. Neurosci. 14(8), 1158–1173 (2014)CrossRefGoogle Scholar
  19. 19.
    Zhen, Q., Huang, D., Wang, Y., Chen, L.: Muscular movement model-based automatic 3D/4D facial expression recognition. IEEE Trans. Multimed. 18(7), 1438–1450 (2016)CrossRefGoogle Scholar
  20. 20.
    Li, H., Sun, J., Xu, Z., Chen, L.: Multimodal 2D+3D facial expression recognition with deep fusion convolutional neural network. IEEE Trans. Multimed. 19(12), 2816–2831 (2017)CrossRefGoogle Scholar
  21. 21.
    Li, H., Sun, J., Chen, L.: Location-sensitive sparse representation of deep normal patterns for expression-robust 3D face recognition. In: 2017 IEEE International Joint Conference on Biometrics (IJCB), pp. 234–242. IEEE (2017)Google Scholar
  22. 22.
    Xue, M., Mian, A., Liu, W., Li, L.: Fully automatic 3D facial expression recognition using local depth features. In: IEEE Winter Conference on Applications of Computer Vision, pp. 1096–1103. IEEE (2014)Google Scholar
  23. 23.
    Hyvarinen, A.: Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans. Neural Netw. 10(3), 626–34 (1999)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Mingliang Xue
    • 1
  • Xiaodong Duan
    • 1
  • Wanquan Liu
    • 2
  • Yuehai Wang
    • 3
  1. 1.Dalian Key Lab of Digital Technology for National Culture, College of Computer Science and EngineeringDalian Minzu UniversityDalianChina
  2. 2.Department of ComputingCurtin UniversityPerthAustralia
  3. 3.School of Electronic Information EngineeringNorth China University of TechnologyBeijingChina

Personalised recommendations