A New Gaze Analysis Based Soft-Biometric

  • Chiara Galdi
  • Michele Nappi
  • Daniel Riccio
  • Virginio Cantoni
  • Marco Porta
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7914)

Abstract

Soft Biometric traits are physical or behavioral human characteristics like skin color, eye color, gait, used by humans to distinguish their peers. However soft biometric characteristics lack in distinctiveness and permanence to identify an individual uniquely and reliably. In this paper a new Gaze Analysis based Soft-biometric (GAS) is investigated. The way an observer looks at a particular subject, was recorded with a remote eye tracker. Feature vectors were built for each observation and used for testing the system as a recognition system. The accuracy of the GAS system was assessed in terms of Receiving Operating Characteristic curves (ROC), Equal Error Rate (EER) and Cumulative Match Curve (CMC), and provided encouraging results.

Keywords

gaze analysis soft biometrics eye tracking 

References

  1. 1.
    Porta, M., Ricotti, S., Jimenez Perez, C.: Emotional E-Learning through Eye Tracking. In: Proc. of the 2012 IEEE International Conference on Collaborative Learning, Marrakesh, Morocco, pp. 1–6 (2012)Google Scholar
  2. 2.
    Cantoni, V., Jimenez Perez, C., Porta, M., Ricotti, S.: Exploiting Eye Tracking in Advanced E-Learning Systems. In: Proceedings of the 13th International Conference on Computer Systems and Technologies (CompSysTech 2012), Rousse, Bulgaria, pp. 376–383 (2012)Google Scholar
  3. 3.
    Perego, E., Del Missier, F., Porta, M., Mosconi, M.: The Cognitive Effectiveness of Subtitle Processing. Media Psychology 13(3), 243–272 (2010)CrossRefGoogle Scholar
  4. 4.
    Duchowski, A.T.: Eye Tracking Methodology – Theory and Practice, 2nd edn. Springer, London (2007)Google Scholar
  5. 5.
    Just, M.A., Carpenter, P.A.: Eye Fixations and Cognitive Processes. Cognitive Psychology 8, 441–480 (1976)CrossRefGoogle Scholar
  6. 6.
    Poole, A., Ball, L.J.: Eye Tracking in Human-Computer Interaction and Usability Research: Current Status and Future Prospects. In: Gahoui, C. (ed.) Encyclopedia of Human-Computer Interaction, pp. 211–219. Idea Group (2006)Google Scholar
  7. 7.
    Itti, L., Koch, C.: A saliency-based search mechanism for overt and covert shifts of visual attention. Vision Research 40, 1489–1506 (2000)CrossRefGoogle Scholar
  8. 8.
    Fookes, C., Maeder, A., Sridharan, S., Mamic, G.: Gaze Based Personal Identification. In: Wang, L., Geng, X. (eds.) Behavioral Biometrics for Human Identification: Intelligent Applications. IGI Global, Hershey (2010)Google Scholar
  9. 9.
    Lagree, S., Bowyer, K.: Predicting ethnicity and gender from iris texture. In: 2011 IEEE International Conference on Technologies for Homeland Security (HST), pp. 440–445 (November 2011)Google Scholar
  10. 10.
    Dantcheva, A., Erdogmus, N., Dugelay, J.-L.: On the reliability of eye color as a soft biometric trait. In: 2011 IEEE Workshop on Applications of Computer Vision (WACV), pp. 227–231 (January 2011)Google Scholar
  11. 11.
    Komogortsev, O.V., Karpov, A., Price, L., Aragon, C.: Biometric authentication via oculomotor plant characteristic. In: Proceedings of the IEEE/IARP International Conference on Biometrics (ICB), pp. 1–8 (2012)Google Scholar
  12. 12.
    Jain, A.K., Dass, S.C., Nandakumar, K.: Soft biometric traits for personal recognition systems. In: Proceedings of International Conference on Biometric Authentication, Hong Kong, pp. 731–738 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Chiara Galdi
    • 1
  • Michele Nappi
    • 1
  • Daniel Riccio
    • 2
  • Virginio Cantoni
    • 3
  • Marco Porta
    • 3
  1. 1.Università degli Studi di SalernoFiscianoItaly
  2. 2.Università degli Studi di Napoli Federico IINapoliItaly
  3. 3.Università degli Studi di PaviaPaviaItaly

Personalised recommendations