Abstract
The reliable estimation of the pupil position is one the most important prerequisites in gaze-based HMI applications. Despite the rich landscape of image-based methods for pupil extraction, tracking the pupil in real-world images is highly challenging due to variations in the environment (e.g. changing illumination conditions, reflection, etc.), in the eye physiology or due to variations related to further sources of noise (e.g., contact lenses or mascara). We present a novel algorithm for robust pupil detection in real-world scenarios, which is based on edge filtering and oriented histograms calculated via the Angular Integral Projection Function. The evaluation on over 38,000 new, hand-labeled eye images from real-world tasks and 600 images from related work showed an outstanding robustness of our algorithm in comparison to the state-of-the-art. Download link (algorithm and data): https://www.ti.uni-tuebingen.de/Pupil-detection.1827.0.html?&L=1.
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References
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(6), 381–395 (1981)
Fitzgibbon, A., Pilu, M., Fisher, R.B.: Direct least square fitting of ellipses. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(5), 476–480 (1999)
Goni, S., Echeto, J., Villanueva, A., Cabeza, R.: Robust algorithm for pupil-glint vector detection in a video-oculography eyetracking system. In: Pattern Recognition. ICPR 2004, vol. 4, pp. 941–944. IEEE (2004)
Kasneci, E.: Towards the Automated Recognition of Assistance Need for Drivers with Impaired Visual Field. Ph.D. thesis, University of Tübingen, Wilhelmstr. 32, 72074 Tübingen (2013)
Kasneci, E., Sippel, K., Aehling, K., Heister, M., Rosenstiel, W., Schiefer, U., Papageorgiou, E.: Driving with Binocular Visual Field Loss? A Study on a Supervised On-road Parcours with Simultaneous Eye and Head Tracking. Plos One (2014). doi:10.1371/journal.pone.0087470
Keil, A., Albuquerque, G., Berger, K., Magnor, M.A.: Real-time gaze tracking with a consumer-grade video camera
Li, D., Winfield, D., Parkhurst, D.J.: Starburst: a hybrid algorithm for video-based eye tracking combining feature-based and model-based approaches. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition-Workshops, 2005. CVPR Workshops, pp. 79–79. IEEE (2005)
Lin, L., Pan, L., Wei, L., Yu, L.: A robust and accurate detection of pupil images. In: 2010 3rd International Conference on Biomedical Engineering and Informatics (BMEI), vol. 1, pp. 70–74. IEEE (2010)
Liu, X., Xu, F., Fujimura, K.: Real-time eye detection and tracking for driver observation under various light conditions. In: IEEE Intelligent Vehicle Symposium, 2002, vol. 2, pp. 344–351. IEEE (2002)
Long, X., Tonguz, O.K., Kiderman, A.: A high speed eye tracking system with robust pupil center estimation algorithm. In: 29th Annual International Conference of the IEEE on Engineering in Medicine and Biology Society. EMBS 2007, pp. 3331–3334. IEEE (2007)
Mohammed, G.J., Hong, B.R., Jarjes, A.A.: Accurate pupil features extraction based on new projection function. Computing and Informatics 29(4), 663–680 (2012)
Peréz, A., Cordoba, M., Garcia, A., Méndez, R., Munoz, M., Pedraza, J.L., Sanchez, F.: A precise eye-gaze detection and tracking system
Schnipke, S.K., Todd, M.W.: Trials and tribulations of using an eye-tracking system. In: CHI 2000 extended abstracts on Human factors in computing systems, pp. 273–274. ACM (2000)
Sippel, K., Kasneci, E., Aehling, K., Heister, M., Rosenstiel, W., Schiefer, U., Papageorgiou, E.: Binocular Glaucomatous Visual Field Loss and Its Impact on Visual Exploration - A Supermarket Study. PLoS ONE 9(8), e106089 (2014)
Świrski, L., Bulling, A., Dodgson, N.: Robust real-time pupil tracking in highly off-axis images. In: Proceedings of the Symposium on Eye Tracking Research and Applications, pp. 173–176. ACM (2012)
Tafaj, E., Kasneci, G., Rosenstiel, W., Bogdan, M.: Bayesian online clustering of eye movement data. In: Proceedings of the Symposium on Eye Tracking Research and Applications, ETRA 2012, pp. 285–288. ACM (2012)
Tafaj, E., Kübler, T.C., Kasneci, G., Rosenstiel, W., Bogdan, M.: Online classification of eye tracking data for automated analysis of traffic hazard perception. In: Mladenov, V., Koprinkova-Hristova, P., Palm, G., Villa, A.E.P., Appollini, B., Kasabov, N. (eds.) ICANN 2013. LNCS, vol. 8131, pp. 442–450. Springer, Heidelberg (2013)
Tafaj, E., Kübler, T., Peter, J., Schiefer, U., Bogdan, M., Rosenstiel, W.: Vishnoo - an open-source software for vision research. In: Proceedings of the \(24^{th}\) IEEE International Symposium on Computer-Based Medical Systems, CBMS 2011, pp. 1–6. IEEE (2011)
Valenti, R., Gevers, T.: Accurate eye center location through invariant isocentric patterns. Transactions on pattern analysis and machine intelligence 34(9), 1785–1798 (2012)
Yuen, H., Illingworth, J., Kittler, J. Ellipse detection using the hough transform. In: Alvey Vision Conference, pp. 1–8 (1988)
Zhu, D., Moore, S.T., Raphan, T.: Robust pupil center detection using a curvature algorithm. Computer methods and programs in biomedicine 59(3), 145–157 (1999)
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Fuhl, W., Kübler, T., Sippel, K., Rosenstiel, W., Kasneci, E. (2015). ExCuSe: Robust Pupil Detection in Real-World Scenarios. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9256. Springer, Cham. https://doi.org/10.1007/978-3-319-23192-1_4
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DOI: https://doi.org/10.1007/978-3-319-23192-1_4
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