An Exploratory Study of Biometrics Using Eye Movement Trajectory Images Collected by Natural Image Stimuli
Resumo
O estudo de movimentos oculares como forma de biometria começou em 2004 e tem como processo típico a captura dos movimentos usando imagens estímulos, tratamento destes dados como sinais no tempo seguido de classificação. Este trabalho propõe dois diferenciais, um é o uso da base de dados DOVES de movimentos oculares coletadas usando-se imagens naturais como estímulo, e o outro é o tratamento dos movimentos oculares como imagens. São geradas imagens das trajetórias dos movimentos oculares, que são a entrada das técnicas HOG e LBP para extração de características, sucedido pelos classificadores SVM, MLP e floresta aleatória. A maior acurácia foi de 33,3% com a combinação das técnicas HOG e MLP, valor comparável com o melhor resultado da competição EMVIC 2014, de 39,6%, que utilizou imagens de faces como estímulo.
Palavras-chave:
Biometria, Movimentos Oculares, Base de dados DOVES, imagens
Referências
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Kasprowski, P. (2004). Human identification using eye movements. Institute of Computer Science.
Kasprowski,P.and Harezlak, K.(2014). The second eye movements verification and identification competition. In Biometrics (IJCB), 2014 IEEE International Joint Con- ference on, pages 1–6. IEEE.
Komogortsev, O. V., Jayarathna, S., Aragon, C. R., and Mahmoud, M. (2010). Biometric identification via an oculomotor plant mathematical model. In Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications, pages 57–60. ACM.
Komogortsev, O. V. and Rigas, I. (2015). BioEye 2015: Competition on biometrics via eye movements. In Biometrics Theory, Applications and Systems (BTAS), 2015 IEEE 7th International Conference on, pages 1–8. IEEE.
Li, C., Xue, J., Quan, C., Yue, J., and Zhang, C. (2018). Biometric recognition via texture features of eye movement trajectories in a visual searching task. PloS one, 13(4):e0194475.
Ojala, T., Pietikainen, M., and Maenpaa, T. (2002). Multiresolution gray-scale and rota- tion invariant texture classification with local binary patterns. IEEE Transactions on pattern analysis and machine intelligence, 24(7):971–987.
Rigas, I., Economou, G., and Fotopoulos, S. (2012). Biometric identification based on the eye movements and graph matching techniques. Pattern Recognition Letters, 33(6):786–792.
Rigas, I., Friedman, L., and Komogortsev, O. (2018). Study of an extensive set of eye mo- vement features: Extraction methods and statistical analysis. Journal of Eye Movement Research, 11(1):3.
Rigas, I. and Komogortsev, O. V. (2014a). Biometric recognition via fixation density maps. In Biometric and Surveillance Technology for Human and Activity Identification XI, volume 9075, page 90750M. International Society for Optics and Photonics.
Rigas, I. and Komogortsev, O. V. (2014b). Biometric recognition via probabilistic spa- tial projection of eye movement trajectories in dynamic visual environments. IEEE Transactions on Information Forensics and Security, 9(10):1743–1754.
Rigas, I. and Komogortsev, O. V. (2017). Current research in eye movement biometrics: An analysis based on BioEye 2015 competition. Image and Vision Computing, 58:129– 141.
Saeed, K. (2016). New directions in behavioral biometrics. CRC Press.
Van Der Linde, I., Rajashekar, U., Bovik, A. C., and Cormack, L. K. (2009). Doves: a database of visual eye movements. Spatial vision, 22(2):161–177.
Zhang, Y., Laurikkala, J., and Juhola, M. (2015). Biometric verification with eye movements: results from a long-term recording series. IET Biometrics, 4(3):162–168.
Brasil, A. R. A., Andrade, J. O., and Komati, K. S. (2020). Eye movements biometrics: A bibliometric analysis from 2004 to 2019. International Journal of Computer Appli- cations, 176(24):1–9.
Dalal, N. and Triggs, B. (2005). Histograms of oriented gradients for human detection. In Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, volume 1, pages 886–893. IEEE.
Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer Society Conference on, volume 1, pages 886–893. IEEE.
Gama, J., Faceli, K., Lorena, A. C., and De Carvalho, A. C. P. L. F. (2011). Inteligência artificial. LTC, Rio de Janeiro.
Holland, C. and Komogortsev, O. V. (2011). Biometric identification via eye movement scanpaths in reading. In 2011 International joint conference on biometrics (IJCB), pages 1–8. IEEE.
Holland, C. D. and Komogortsev, O. V. (2013). Complex eye movement pattern bio- metrics: Analyzing fixations and saccades. In Biometrics (ICB), 2013 International Conference on, pages 1–8. IEEE.
Jain, A. K., Flynn, P., and Ross, A. A. (2007). Handbook of biometrics. Springer Science & Business Media.
Kasprowski, P. (2004). Human identification using eye movements. Institute of Computer Science.
Kasprowski,P.and Harezlak, K.(2014). The second eye movements verification and identification competition. In Biometrics (IJCB), 2014 IEEE International Joint Con- ference on, pages 1–6. IEEE.
Komogortsev, O. V., Jayarathna, S., Aragon, C. R., and Mahmoud, M. (2010). Biometric identification via an oculomotor plant mathematical model. In Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications, pages 57–60. ACM.
Komogortsev, O. V. and Rigas, I. (2015). BioEye 2015: Competition on biometrics via eye movements. In Biometrics Theory, Applications and Systems (BTAS), 2015 IEEE 7th International Conference on, pages 1–8. IEEE.
Li, C., Xue, J., Quan, C., Yue, J., and Zhang, C. (2018). Biometric recognition via texture features of eye movement trajectories in a visual searching task. PloS one, 13(4):e0194475.
Ojala, T., Pietikainen, M., and Maenpaa, T. (2002). Multiresolution gray-scale and rota- tion invariant texture classification with local binary patterns. IEEE Transactions on pattern analysis and machine intelligence, 24(7):971–987.
Rigas, I., Economou, G., and Fotopoulos, S. (2012). Biometric identification based on the eye movements and graph matching techniques. Pattern Recognition Letters, 33(6):786–792.
Rigas, I., Friedman, L., and Komogortsev, O. (2018). Study of an extensive set of eye mo- vement features: Extraction methods and statistical analysis. Journal of Eye Movement Research, 11(1):3.
Rigas, I. and Komogortsev, O. V. (2014a). Biometric recognition via fixation density maps. In Biometric and Surveillance Technology for Human and Activity Identification XI, volume 9075, page 90750M. International Society for Optics and Photonics.
Rigas, I. and Komogortsev, O. V. (2014b). Biometric recognition via probabilistic spa- tial projection of eye movement trajectories in dynamic visual environments. IEEE Transactions on Information Forensics and Security, 9(10):1743–1754.
Rigas, I. and Komogortsev, O. V. (2017). Current research in eye movement biometrics: An analysis based on BioEye 2015 competition. Image and Vision Computing, 58:129– 141.
Saeed, K. (2016). New directions in behavioral biometrics. CRC Press.
Van Der Linde, I., Rajashekar, U., Bovik, A. C., and Cormack, L. K. (2009). Doves: a database of visual eye movements. Spatial vision, 22(2):161–177.
Zhang, Y., Laurikkala, J., and Juhola, M. (2015). Biometric verification with eye movements: results from a long-term recording series. IET Biometrics, 4(3):162–168.
Publicado
30/06/2020
Como Citar
BRASIL, Antonio; ANDRADE, Jefferson ; PINTO, Luiz; KOMATI, Karin .
An Exploratory Study of Biometrics Using Eye Movement Trajectory Images Collected by Natural Image Stimuli. In: SEMINÁRIO INTEGRADO DE SOFTWARE E HARDWARE (SEMISH), 47. , 2020, Cuiabá.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 25-36.
ISSN 2595-6205.
DOI: https://doi.org/10.5753/semish.2020.11314.
