Advertisement

Performance Evaluation of Face Classification Systems

  • Giovanni Betta
  • Domenico Capriglione
  • Mariella Corvino
  • Michele Gasparetto
  • Consolatina Liguori
  • Alfredo Paolillo
  • Emanuele Zappa
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 362)

Abstract

In this paper face classification systems based on 3D images are compared in terms of classification and metrological performance in presence of image uncertainty. In previous papers the authors proposed a new approach to classification and recognition problems. It is based on the evaluation of the image uncertainty and on the exploitation of such information to provide the confidence level of classification results. Such approach is here adopted for comparing several 3D architectures, different for camera specifications and geometrical positioning, with the aims of quantifying their performance from a metrological point of view and of identifying the configuration able to optimize the result reliability.

Keywords

Face Recognition Measurement Uncertainty Classification Performance Facial Image Classification Procedure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Phillips, P.J., Flynn, P.J., Scruggs, T., Bowyer, K.W., Chang, J., Hoffman, K., Marques, J., Jaesik, M., Worek, W.: Overview of the face recognition grand challenge. In Proceedings of IEEE Computer Vision and Pattern Recognition Conference, pp. 947–954 (2005)Google Scholar
  2. 2.
    Zhao, W., Chellapa, R., Phillips, P.J., Rosefeld, A.: Face recognition: a literature survey. J. ACM Comput. Surv., 399–458 (2003)Google Scholar
  3. 3.
    Gross, R., Shi, J., Cohn, J.: Quo vadis face recognition? Report of Robotics Institute of Carnegie Mellon University (2001) Google Scholar
  4. 4.
    Hea, Y., Zhao, L., Zou, C.: Face recognition using common faces method. Pattern Recogn., 2218–2222 (2006)Google Scholar
  5. 5.
    Betta, G., Capriglione, D., Crenna, F., Gasparetto, M., Liguori, C., Paolillo, A., Rossi, G.B., Zappa, E.: Face-based recognition techniques: proposals for the metrological characterization of global and feature-based approaches. Meas. Sci. Technol. 22(12) (2011)Google Scholar
  6. 6.
    Jain, A.K., Duin, R.P.W., Mao, J.: Statistical pattern recognition: a review. IEEE Trans. Pattern Anal. Mach. Intell. 22(1), 4–37 (2000)CrossRefGoogle Scholar
  7. 7.
    Gianfelici, F., Turchetti, C., Crippa, P.: A non-probabilistic recognizer of stochastic signals based on KLT. Sig. Process. 89(4), 422–437 (2009)CrossRefzbMATHGoogle Scholar
  8. 8.
    Zappa, E., Testa, R., Barbesta, M., Gasparetto, M.: Uncertainty of 3D facial features measurements and its effects on personal identification. Measurement (2014)Google Scholar
  9. 9.
    Crenna, F., Zappa, E., Bovio, L., Testa, R., Gasparetto, M., Rossi, G.B.: Implementation of perceptual aspects in a face recognition algorithm. J. Phys. Conf. Ser. 459, 012031 (2013). doi: 10.1088/1742-6596/459/1/012031 CrossRefGoogle Scholar
  10. 10.
    Zhang, G.: Face recognition based on fuzzy linear discriminant analysis. IERI Procedia 2, 873–879 (2012)CrossRefGoogle Scholar
  11. 11.
    Aisjah, A.S., Arifin, S.: Maritime weather prediction using fuzzy logic in Java sea for shipping feasibility. Int. J. Artif Intell. 10(S13), 112–122 (2013)Google Scholar
  12. 12.
    Zhang, D., Wang, Q-G., Yu, L., Song, H.: Fuzzy-model based fault detection for a class of nonlinear systems with networked measurements. IEEE Trans. Instrum. Meas. 62(12), 3148–3159 (2013)Google Scholar
  13. 13.
    Yager, R.R.: On the fusion of imprecise uncertainty measures using belief structures. Inf. Sci. 181(15), 3199–3209 (2011)MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    JCGM 100.: Evaluation of measurement data—guide to the expression of uncertainty in measurement. ISO-GUM (2008)Google Scholar
  15. 15.
    Betta, G., Capriglione, D., Corvino, M., Liguori, C., Paolillo, A.: Face based recognition algorithms: a first step toward a metrological characterization. IEEE Trans. Instrum. Meas. 62(5), 1008–1016, art. no. 6493520 (2013)Google Scholar
  16. 16.
    Betta, G., Capriglione, D., Corvino, M., Liguori, C., Paolillo, A.: Face based recognition algorithms: the use of uncertainty in the classification. IEEE Proc. I2MTC13, 1098–1103 (2013)Google Scholar
  17. 17.
    Betta et alii, G.: Managing the uncertainty for face classification with 3D features. IEEE Proc. I2MTC14, 412–417 (2014)Google Scholar
  18. 18.
    Betta, G., Capriglione, D., Corvino, M., Liguori, C., Paolillo, A.: A proposal for the management of the measurement uncertainty in classification and recognition problems. IEEE Trans. Instrum Meas. (2014). doi: 10.1109/TIM.2014.2347218
  19. 19.
    Cootes, T.F., Gareth, J.E., Christopher, J.T.: Active appearance models. IEEE Trans. Pattern Anal. Mach. Intell. 23(6), 681–685 (2001)CrossRefGoogle Scholar
  20. 20.
    Zappa, E., Mazzoleni, P.: Reliability of personal identification base on optical 3D measurement of a few facial landmarks. Proc. Comput. Sci., 2769–2777 (2010)Google Scholar
  21. 21.
    Zappa, E., Mazzoleni, P., Hai, Y.: Stereoscopy based 3D face recognition system. Procedia Comput. Sci. 1(1), 2521–2528 (2010)CrossRefGoogle Scholar
  22. 22.
    Liguori, C., Paolillo, A., Pietrosanto, A.: A discussion about stereo vision techniques for industrial image-based measurement systems. In: Proceedings of the 20th IEEE Instrumentation and Measurement Technology Conference IMTC '03, vol. 1, pp. 77–82 (2003)Google Scholar
  23. 23.
    Di Leo, G., Liguori, C., Pietrosanto, A., Paciello, V., Paolillo, A.: Illumination design in vision-based measurement systems. In: Proceedings of the IEEE International Instrumentation and Measurement Technology Conference (I2MTC), pp. 1491–1495 (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Giovanni Betta
    • 1
  • Domenico Capriglione
    • 1
  • Mariella Corvino
    • 1
  • Michele Gasparetto
    • 2
  • Consolatina Liguori
    • 3
  • Alfredo Paolillo
    • 3
  • Emanuele Zappa
    • 2
  1. 1.DIEIUniversity of Cassino and of Southern LazioCassinoItaly
  2. 2.Department of Mechanical EngineeringPolitecnico di MilanoMilanoItaly
  3. 3.DIInUniversity of SalernoFiscianoItaly

Personalised recommendations