Eyes Closeness Detection Using Appearance Based Methods

  • Xue Liu
  • Xiaoyang Tan
  • Songcan Chen
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 385)


Human eye closeness detection has gained wide applications in human computer interface designation, facial expression recognition, driver fatigue detection, and so on. In this work, we present an extensive comparison on several state of art appearance-based eye closeness detection methods, with emphasize on the role played by each crucial component, including geometric normalization, feature extraction, and classification. Three conclusions are highlighted through our experimental results: 1) fusing multiple cues significantly improves the performance of the detection system; 2) the AdaBoost classifier with difference of intensity of pixels is a good candidate scheme in practice due to its high efficiency and good performance; 3) eye alignment is important and influences the detection accuracy greatly. These provide useful lessons for the future investigations on this interesting topic.


Eye closeness detection Eye state measurement 


  1. 1.
    Noor, H., Ibrahim, R.: A framework for measurement of humans fatigue level using 2 factors. In: International Conference on Computer and Communication Engineering, pp. 414–418 (2008)Google Scholar
  2. 2.
    Eriksson, M., Papanikotopoulos, N.: Eye-tracking for detection of driver fatigue. In: IEEE Conference on Intelligent Transportation System (TSC), pp. 314–319 (1997)Google Scholar
  3. 3.
    Mitelman, R., Joshua, M., Adler, A., Bergman, H.: A noninvasive, fast and inexpensive tool for the detection of eye open/closed state in primates. Journal of Neuroscience Methods 178, 350–356 (2009)CrossRefGoogle Scholar
  4. 4.
    Sun, R., Ma, Z.: Robust and efficient eye location and its state detection. Advances in Computation and Intelligence, pp. 318–326 (2009)Google Scholar
  5. 5.
    Valenti, R., Gevers, T.: Accurate eye center location and tracking using isophote curvature. In: Computer Vision and Pattern Recognition (CVPR), pp. 1–8 (2008)Google Scholar
  6. 6.
    Wang, H., Zhou, L., Ying, Y.: A novel approach for real time eye state detection in fatigue awareness system. In: Robotics Automation and Mechatronics (RAM), pp. 528–532 (2010)Google Scholar
  7. 7.
    Jiao, F., He, G.: Real-time eye detection and tracking under various light conditions. Data Science Journal 6, 636–640 (2007)CrossRefGoogle Scholar
  8. 8.
    Orozco, J., Roca, F., Gonzàlez, J.: Real-time gaze tracking with appearance-based models. Machine Vision and Applications 20, 353–364 (2009)CrossRefGoogle Scholar
  9. 9.
    Li, S., Chu, R., Liao, S., Zhang, L.: Illumination invariant face recognition using near-infrared images. IEEE Transactions on Pattern Analysis and Machine Intelligence 29, 627–639 (2007)CrossRefGoogle Scholar
  10. 10.
    Liu, Z., Ai, H.: Automatic eye state recognition and closed-eye photo correction. Pattern Recognition, 1–4 (2008)Google Scholar
  11. 11.
    Dehnavi, M., Eshghi, M.: Design and implementation of a real time and train less eye state recognition system. EURASIP Journal on Advances in Signal Processing 30 (2012)Google Scholar
  12. 12.
    Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7), 971–987 (2002)CrossRefGoogle Scholar
  13. 13.
    Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: Computer Vision and Pattern Recognition (CVPR), pp. 886–893 (2005)Google Scholar
  14. 14.
    Cheng, E., Kong, B., Hu, R., Zheng, F.: Eye state detection in facial image based on linear prediction error of wavelet coefficients. In: IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 1388–1392 (2009)Google Scholar
  15. 15.
    Zhou, L., Wang, H.: Open/closed eye recognition by local binary increasing intensity patterns. In: Robotics Automation and Mechatronics (RAM), pp. 7–11 (2011)Google Scholar
  16. 16.
    Wang, Q., Yang, J.: Eye location and eye state detection in facial images with unconstrained background. J. Info. & Comp. Science 1, 284–289 (2006)Google Scholar
  17. 17.
    Viola, P., Jones, M.: Robust real-time face detection. International Journal of Computer Vision 57, 137–154 (2007)CrossRefGoogle Scholar
  18. 18.
    Tan, X., Song, F., Zhou, Z., Chen, S.: Enhanced pictorial structures for precise eye localization under incontrolled conditions. In: Computer Vision and Pattern Recognition (CVPR), pp. 1621–1628 (2009)Google Scholar
  19. 19.
    Huang, G., Jain, V., Learned-Miller, E.: Unsupervised joint alignment of complex images. In: International Conference on Computer Vision (ICCV), pp. 1–8 (2007)Google Scholar
  20. 20.
    Lades, M., Vorbruggen, J., Buhmann, J., Lange, J., von der Malsburg, C., Wurtz, R., Konen, W.: Distortion invariant object recognition in the dynamic link architecture. IEEE Transactions on Computers 42(3), 300–311 (1993)CrossRefGoogle Scholar
  21. 21.
    Chang, C., Lin, C.: Libsvm: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology 2, 27 (2011)Google Scholar
  22. 22.
    Baluja, S., Sahami, M., Rowley, H.: Efficient face orientation discrimination. In: International Conference on Image Processing (ICIP), pp. 589–592 (2004)Google Scholar
  23. 23.
    Baluja, S., Rowley, H.: Boosting sex identification performance. International Journal of Computer Vision 71, 111–119 (2007)CrossRefGoogle Scholar
  24. 24.
  25. 25.
    Tan, X., Triggs, B.: Fusing Gabor and LBP Feature Sets for Kernel-Based Face Recognition. In: Zhou, S.K., Zhao, W., Tang, X., Gong, S. (eds.) AMFG 2007. LNCS, vol. 4778, pp. 235–249. Springer, Heidelberg (2007)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2012

Authors and Affiliations

  • Xue Liu
    • 1
  • Xiaoyang Tan
    • 1
  • Songcan Chen
    • 1
  1. 1.College of Computer Science & TechnologyNanjing University of Aeronautics & AstronauticsP.R. China

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