Abstract
While pupil tracking under active infrared illumination is now relatively well-established, current iris tracking algorithms often fail due to several non-ideal conditions. In this paper, we present a novel approach for tracking the iris. We introduce a radial symmetry detector into the proposal distribution to guide the particles towards the high probability region. Experimental results demonstrate the ability of the proposed particle filter to robustly track the iris in challenging conditions, such as complex dynamics. Compared to some previous methods, our iris tracker is also able to automatically recover from failure.
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References
Duchowski, A.T.: A breadth-first survey of eye-tracking applications. Behavior Research Methods, Instruments & Computers 34, 455–470 (2002)
Hansen, D.W., Ji, Q.: In the eye of the beholder: A survey of models for eyes and gaze. IEEE Trans. on PAMI 32, 478–500 (2010)
Li, D., Winfield, D., Parkhurst, D.J.: Starburst: A hybrid algorithm for video-based eye tracking combining feature-based and model-based approaches. In: Proc. of CVPR, pp. 79–86 (2005)
Li, D., Parkhurst, D.: Open-source software for real-time visible-spectrum eye tracking. In: COGAIN, pp. 18–20 (2006)
Colombo, C., Comanducci, D., Del, B.: Robust iris localization and tracking based on constrained visual fitting. In: Proc. of ICIAP, pp. 454–460 (2007)
Ryan, W.J., Duchowski, A.T., Birchfield, S.T.: Limbus/pupil switching for wearable eye tracking under variable lighting conditions. In: Proc. of ETRA, pp. 61–64 (2008)
Ryan, W.J., Duchowski, A.T., Vincent, E.A., Battisto, D.: Match-moving for area-based analysis of eye movements in natural tasks. In: Proc. of ETRA, pp. 235–242 (2010)
Hansen, D.W., Pece, A.E.C.: Iris tracking with feature free contours. In: Proc. of AMFG, pp. 208–214 (2003)
Wu, H., Kitagawa, Y., Wada, T., Kato, T., Chen, Q.: Tracking iris contour with a 3D eye-model for gaze estimation. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds.) ACCV 2007, Part I. LNCS, vol. 4843, pp. 688–697. Springer, Heidelberg (2007)
Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM 24, 381–395 (1981)
Pece, A.E.C., Worrall, A.D.: Tracking with the em contour algorithm. In: Proc. of ECCV, pp. 3–17 (2002)
Loy, G., Zelinsky, A.: Fast radial symmetry for detecting points of interest. IEEE Trans. on PAMI 25, 959–973 (2003)
Isard, M., Blake, A.: Condensation - conditional density propagation for visual tracking. IJCV 29, 5–28 (1998)
Okuma, K., Taleghani, A., De Freitas, N., Little, J.J., Lowe, D.G.: A boosted particle filter: Multitarget detection and tracking. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3021, pp. 28–39. Springer, Heidelberg (2004)
Zhang, W., Li, B., Ye, X., Zhuang, Z.: A robust algorithm for iris localization based on radial symmetry. In: Proc. of CISW, pp. 324–327 (2007)
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Martinez, F., Carbone, A., Pissaloux, E. (2011). Radial Symmetry Guided Particle Filter for Robust Iris Tracking. In: Real, P., Diaz-Pernil, D., Molina-Abril, H., Berciano, A., Kropatsch, W. (eds) Computer Analysis of Images and Patterns. CAIP 2011. Lecture Notes in Computer Science, vol 6855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23678-5_63
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DOI: https://doi.org/10.1007/978-3-642-23678-5_63
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