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International Conference on Advanced Concepts for Intelligent Vision Systems

ACIVS 2015: Advanced Concepts for Intelligent Vision Systems pp 391–402Cite as

Soft Biometrics by Modeling Temporal Series of Gaze Cues Extracted in the Wild

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9386))

Abstract

Soft biometric systems have spread among recent years, both for powering classical biometrics, as well as stand alone solutions with several application scopes ranging from digital signage to human-robot interaction. Among all, in the recent years emerged the possibility to consider as a soft biometrics also the temporal evolution of the human gaze and some recent works in the literature explored this exciting research line by using expensive and (perhaps) unsafe devices which, moreover, require user cooperation to be calibrated. By our knowledge the use of a low-cost, non-invasive, safe and calibration-free gaze estimator to get soft-biometrics data has not been investigated yet. This paper fills this gap by analyzing the soft-biometrics performances obtained by modeling the series of gaze estimated by exploiting the combination of head poses and eyes’ pupil locations on data acquired by an off-the-shelf RGB-D device.

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References

  1. Bekios-Calfa, J., Buenaposada, J.M., Baumela, L.: Robust gender recognition by exploiting facial attributes dependencies. Pattern Recognition Letters 36, 228–234 (2014)

    Article  Google Scholar 

  2. Busjahn, T., Schulte, C., Sharif, B., Begel, A., Hansen, M., Bednarik, R., Orlov, P., Ihantola, P., Shchekotova, G., Antropova, M., et al.: Eye tracking in computing education. In: Proceedings of the Tenth Annual Conference on International Computing Education Research, pp. 3–10. ACM (2014)

    Google Scholar 

  3. Campisi, P.: Security and Privacy in Biometrics. Springer (2013)

    Google Scholar 

  4. Cantoni, V., Galdi, C., Nappi, M., Porta, M., Riccio, D.: Gant: Gaze analysis technique for human identification. Pattern Recognition 48(4), 1027–1038 (2015)

    Article  Google Scholar 

  5. Cazzato, D., Leo, M., Distante, C.: An investigation on the feasibility of uncalibrated and unconstrained gaze tracking for human assistive applications by using head pose estimation. Sensors 14(5), 8363–8379 (2014)

    Article  Google Scholar 

  6. Deravi, F., Guness, S.P.: Gaze trajectory as a biometric modality. In: BIOSIGNALS, pp. 335–341 (2011)

    Google Scholar 

  7. Fernández, C., Huerta, I., Prati, A.: A comparative evaluation of regression learning algorithms for facial age estimation. In: Ji, Q., B. Moeslund, T., Hua, G., Nasrollahi, K. (eds.) FFER 2014. LNCS, vol. 8912, pp. 133–144. Springer, Heidelberg (2015)

    Google Scholar 

  8. Guo, G., Mu, G.: Joint estimation of age, gender and ethnicity: CCA vs. PLS. In: 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG), pp. 1–6. IEEE (2013)

    Google Scholar 

  9. Hong, L., Jain, A.K., Pankanti, S.: Can multibiometrics improve performance? In: Proceedings AutoID, vol. 99, pp. 59–64. Citeseer (1999)

    Google Scholar 

  10. Jain, A.K., Dass, S.C., Nandakumar, K.: Soft biometric traits for personal recognition systems. In: Zhang, D., Jain, A.K. (eds.) ICBA 2004. LNCS, vol. 3072, pp. 731–738. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  11. Jain, A.K., Ross, A., Prabhakar, S.: An introduction to biometric recognition. IEEE Transactions on Circuits and Systems for Video Technology 14(1), 4–20 (2004)

    Article  Google Scholar 

  12. Kalman, R.E.: A new approach to linear filtering and prediction problems. Journal of Fluids Engineering 82(1), 35–45 (1960)

    Google Scholar 

  13. Kasprowski, P., Komogortsev, O.V., Karpov, A.: First eye movement verification and identification competition at BTAS 2012. In: 2012 IEEE Fifth International Conference on Biometrics: Theory, Applications and Systems (BTAS), pp. 195–202. IEEE (2012)

    Google Scholar 

  14. Kumar, A., Wong, D.C., Shen, H.C., Jain, A.K.: Personal verification using palmprint and hand geometry biometric. In: Kittler, J., Nixon, M.S. (eds.) AVBPA 2003. LNCS, vol. 2688, pp. 668–678. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  15. Leo, M., Cazzato, D., De Marco, T., Distante, C.: Unsupervised eye pupil localization through differential geometry and local self-similarity matching. PloS one 9(8), e102829 (2014)

    Article  Google Scholar 

  16. Parris, E.S., Carey, M.J.: Language independent gender identification. In: Proceedings of the 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP 1996, vol. 2, pp. 685–688. IEEE (1996)

    Google Scholar 

  17. Rabiner, L.: A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE 77(2), 257–286 (1989)

    Article  Google Scholar 

  18. Roy, A., Halevi, T., Memon, N.: An HMM-based behavior modeling approach for continuous mobile authentication. In: 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3789–3793. IEEE (2014)

    Google Scholar 

  19. Stiefelhagen, R., Zhu, J.: Head orientation and gaze direction in meetings. In: CHI 2002 Extended Abstracts on Human Factors in Computing Systems, pp. 858–859. ACM (2002)

    Google Scholar 

  20. Sun, L., Liu, Z., Sun, M.T.: Real time gaze estimation with a consumer depth camera. Information Sciences (2015)

    Google Scholar 

  21. Wang, X., Ly, V., Lu, G., Kambhamettu, C.: Can we minimize the influence due to gender and race in age estimation? In: 2013 12th International Conference on Machine Learning and Applications (ICMLA), vol. 2, pp. 309–314. IEEE (2013)

    Google Scholar 

  22. Wildes, R.P.: Iris recognition: an emerging biometric technology. Proceedings of the IEEE 85(9), 1348–1363 (1997)

    Article  Google Scholar 

  23. Xiong, X., Cai, Q., Liu, Z., Zhang, Z.: Eye gaze tracking using an RGBD camera: a comparison with a RGB solution. In: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication, pp. 1113–1121. ACM (2014)

    Google Scholar 

  24. Ye, Z., Mohamadian, H., Ye, Y.: Information measures for biometric identification via 2d discrete wavelet transform. In: IEEE International Conference on Automation Science and Engineering. CASE 2007, pp. 835–840. IEEE (2007)

    Google Scholar 

  25. Yoon, H.J., Carmichael, T.R., Tourassi, G.: Gaze as a biometric. In: SPIE Medical Imaging, pp. 903707–903707. International Society for Optics and Photonics (2014)

    Google Scholar 

  26. YouTube: Video (2015). https://www.youtube.com/watch?v=KnJtsZzMJ8Y

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Author information

Authors and Affiliations

  1. National Research Council of Italy - Institute of Optics, Arnesano, LE, Italy

    Marco Leo & Cosimo Distante

  2. Faculty of Engineering, University of Salento, Lecce, Italy

    Dario Cazzato & Andrea Evangelista

Authors
  1. Dario Cazzato
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  2. Marco Leo
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  3. Andrea Evangelista
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  4. Cosimo Distante
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Corresponding author

Correspondence to Dario Cazzato .

Editor information

Editors and Affiliations

  1. Dipartimento di Matematica e Informatica, Università di Catania, Catania, Catania, Italy

    Sebastiano Battiato

  2. Arcueil CX, France

    Jacques Blanc-Talon

  3. Catania, Italy

    Giovanni Gallo

  4. Gent, Belgium

    Wilfried Philips

  5. CSIRO, Sydney, New South Wales, Australia

    Dan Popescu

  6. Vision Lab., University of Antwerp, Antwerpen, Belgium

    Paul Scheunders

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© 2015 Springer International Publishing Switzerland

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Cazzato, D., Leo, M., Evangelista, A., Distante, C. (2015). Soft Biometrics by Modeling Temporal Series of Gaze Cues Extracted in the Wild. In: Battiato, S., Blanc-Talon, J., Gallo, G., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2015. Lecture Notes in Computer Science(), vol 9386. Springer, Cham. https://doi.org/10.1007/978-3-319-25903-1_34

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  • DOI: https://doi.org/10.1007/978-3-319-25903-1_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25902-4

  • Online ISBN: 978-3-319-25903-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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