Skip to main content
Log in

Expressions Recognition of North-East Indian (NEI) Faces

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Facial expression is one of the major distracting factors for face recognition performance. Pose and illumination variations on face images also influence the performance of face recognition systems. The combination of three variations (facial expression, pose and illumination) seriously degrades the recognition accuracy. In this paper, three experimental protocols are designed in such a way that the successive performance degradation due to the increasing variations (expressions, expressions with illumination effect and expressions with illumination and pose effect) on face images can be examined. The whole experiment is carried out using North-East Indian (NEI) face images with the help of four well-known classification algorithms namely Linear Discriminant Analysis (LDA), K-Nearest Neighbor algorithm (KNN), combination of Principal Component Analysis and Linear Discriminant Analysis (PCA + LDA), combination of Principal Component Analysis and K-Nearest Neighbor algorithm (PCA + KNN). The experimental observations are analyzed through confusion matrices and graphs. This paper also describes the creation of NEI facial expression database, which contains visual static face images of different ethnic groups of the North-East states. The database is useful for future researchers in the area of forensic science, medical applications, affective computing, intelligent environments, lie detection, psychiatry, anthropology, etc.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. Bhowmik MK, Saha K, Saha P, Bhattacharjee D (2014) DeitY-TU face database: its design, multiple cameras capturing, characteristics, and evaluation. Opt Eng 53(10):102106-1–102106-24. doi:10.1117/1.OE.53.10.102106

    Article  Google Scholar 

  2. Cao B, Shan S, Zhang X, Gao W (2004) Baseline evaluations on the CAS-PEAL-R1 face database. In: Proc. 5th Chinese Conf on Biometric Recognition, Guangzhou, China, pp. 370–378. doi: 10.1007/978-3-540-30548-4_42

  3. Dasarathy BV (1990) Nearest neighbor (NN) norms: NN pattern classification techniques. IEEE Computer Society Press, Los Alamitos

    Google Scholar 

  4. Ekman P (1972) Universals and cultural differences in facial expressions of emotion. In: Cole J (ed) Nebraska sym. on motivation. University of Nebraska Press, Lincoln, pp 207–283

    Google Scholar 

  5. Ekman P (1993) Facial expression and emotion. Am Psychol 48:384–392

    Article  Google Scholar 

  6. Gross R (2005) Face databases. In: Li SZ, Jain A (eds) Handbook of face recognition. Springer, New York, pp 301–328

    Chapter  Google Scholar 

  7. Gross R, Matthews I, Cohn J, Kanade T, Baker S (2010) Multi-PIE. Image Vis Comput 28(5):807–813. doi:10.1016/j.imavis.2009.08.002

    Article  Google Scholar 

  8. Langner O, Dotsch R, Bijlstra G, Wigboldus DHJ, Hawk ST, van Knippenberg A (2010) Presentation and validation ofthe Radboud faces database. Cognit Emot 24(8):1377–1388. doi:10.1080/02699930903485076

    Article  Google Scholar 

  9. Li T, Zhu S, Ogihara M (2006) Using discriminant analysis for multi-class classification: an experimental investigation. Knowl Inf Syst 10(4):453–472. doi:10.1007/s10115-006-0013-y

    Article  Google Scholar 

  10. Lucey P, Cohn JF, Kanade T, Saragih J, Ambadar J, Matthews I (2010) The extended Cohn-Kanade dataset (CK+): a complete dataset for action unit and emotion-specified expression. Proc. IEEE Int Conf on Computer Vision and Pattern Recognition Workshop, San Francisco

    Google Scholar 

  11. Lyons MJ, Akamatsu S, Kamachi M, Gyoban J (1998) Coding facial expressions with Gabor wavelets. Proc. 3rd IEEE Int Conf on Automatic Face and Gesture Recognition, Nara, pp 200–205

    Google Scholar 

  12. Majumder G, Debnath R, Bhowmik MK, Bhattacharjee D, Nasipuri M (2012) Image registration of North-Eastern Indian (NEI) face database. Proc 1st Int Conf on Intelligent Infrastructure, Kolkata, pp 286–290

    Google Scholar 

  13. Martinez AM, Benavente R (1998) The AR face database. CVC Technical Report #24. Computer Vision Center, Barcelona, Spain

  14. Pantic M, Valstar M, Rademaker R, Maat L (2005) Web-based database for facial expression analysis. Proc. IEEE Int Conf on Multimedia and Expo (ICME05), Amsterdam, pp 317–321

    Google Scholar 

  15. Roh M-C, Lee S—W (2007) Performance analysis of face recognition algorithms on Korean face database. Int J Pattern Recognit Artif Intell 21(6):1017–1033. doi:10.1142/S0218001407005818

    Article  Google Scholar 

  16. Sim T, Baker S, Bsat M (2003) The CMU pose, illumination, and expression database. IEEE Trans Pattern Anal Mach Intell 25(12):1615–1618. doi:10.1109/TPAMI.2003.1251154

    Article  Google Scholar 

  17. Turk M, Pentland A (1991) Eigenfaces for recognition. J Cogn Neurosci 3(1):71–86

    Article  Google Scholar 

Download references

Acknowledgment

The work presented here is being conducted in the Biometrics Laboratory of Tripura University, under the research project supported by the Grant No. 12(2)/2011-ESD, dated 29/03/2011, from DeitY, MCIT, Government of India. The first author is grateful to Department of Science and Technology (DST), Government of India for providing her Junior Research Fellowship-Professional (JRF-Professional) under DST INSPIRE fellowship program (No. IF131067). The authors would like to thank anonymous reviewers for their comments/suggestions to improve the quality of the paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mrinal Kanti Bhowmik.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Saha, P., Bhowmik, M.K., Bhattacharjee, D. et al. Expressions Recognition of North-East Indian (NEI) Faces. Multimed Tools Appl 75, 16781–16807 (2016). https://doi.org/10.1007/s11042-015-2945-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-015-2945-2

Keywords

Navigation