Abstract
In this paper, we propose a vision-based real time algorithm for driver fatigue detection. Face and eyes of the driver are first localized and then marked in every frame obtained from the video source. The eyes are tracked in real time using correlation function with an automatically generated online template. The proposed algorithm can detect eyelids movement and can classify whether the eyes are open or closed by using normalized cross correlation function based classifier. If the eyes are closed for more than a specified time an alarm is generated. The accuracy of algorithm is demonstrated using real data under varying conditions for people with different gender, skin colors, eye shapes and facial hairs.
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References
Brandt, T., Stemmer, R., Rakotonirainy, A.: Affordable visual driver monitoring system for fatigue and monotony. IEEE International Conference on Systems, Man and Cybernetics 7, 6451–6456 (2004)
Bagci, A.M., Ansari, R., Khokhar, A., Cetin, E.: Eye tracking using Markov models. In: Proceedings of the 17th International Conference on Pattern Recognition, vol. 3, pp. 818–821 (2004)
Goudail, F., Lange, E., Iwamoto, T., Kyuma, K., Otsu, N.: Face recognition system using local autocorrelations and multiscaleintegration. IEEE Transactions on Pattern Analysis and Machine Intelligence 18, 1024–1028 (1996)
Beymer, D., Flickner, M.: Eye gaze tracking using an active stereo head. In: Proceedings of the 2003 IEEE Computer Society on Computer Vision and Pattern Recognition (CVPR 2003), San Jose, CA, USA (2003)
Viola, P., Jones, J.: Robust Real-Time Face Detection. International Journal of Computer Vision 57(2), 137–154 (2004)
Garcia, C., Tziritas, G.: Face detection using quantized skin color regions merging and wavelet packet analysis. IEEE Transactions on Multimedia 1(3), 264–277 (1999)
Singh, S.K., Chauhan, D.S., Vatsa, M., Singh, R.: A Robust Skin Color Based Face Detection Algorithm. Tamkang Journal of Science and Engineering 6, 227–234 (2003)
Singh, S., Papanikolopoulos, N.: Monitoring Driver Fatigue Using Facial Analysis Technique. In: Proceedings of International Conference on Intelligent Transportation Systems, Tokyo, Japan, pp. 314–318 (1999)
Feris, R.S., Emidio de Campos, T., Cesar Junior, R.M.: Detection and Tracking of Facial Features in Video Sequences. In: Proceedings of the Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence, vol. 1793, pp. 127–135 (2000)
Rowley, H., Baluja, S., Kanade, T.: Neural Network-Based Face Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 20, 23–28 (1998)
Lee, S.-J., Jung, S.-B., Kwon, J.-W., Seung-Hong: Face detection and recognition using PCA. In: Proceedings of the IEEE Region 10 Conference, vol. 1, pp. 84–87 (1999)
Huang, J., Shao, X., Wechsler, H.: Pose discrimination and eye detection using support vector machines (SVMs). In: Proceeding of NATO-ASI on Face Recognition, From Theory to Applications, pp. 528–536
Cherif, R.Z., Nat-Ali, A., Krebs, M.O.: An adaptive calibration of an infrared light device used for gaze tracking. In: Proceedings of the 19th IEEE Instrumentation and Measurement Technology Conference, Anchorage, AK, USA (2000)
Morimoto, C., Flickner, M.: Real-time multiple face detection using active illumination, Federal Highway Administration, Office of Motor Carriers (1998)
Morimoto, C.H., Flickner, M.: Real-time multiple face detection using active illumination. In: IEEE conference on Face and Gesture Recognition, pp. 8–13 (2000)
Ramadan, S., Abd-Almageed, W., Smith, C.E.: Eye Tracking Using Active Deformable Models. In: The III Indian Conference on Computer Vision, Graphics and Image processing, India (2002)
Artaud, P., Planque, S., Lavergne, C., Cara, H., de Lepine, P., Tarriere, C., Gueguen, B.: An on-board system for detecting lapses of alertness in car driving. In: Proceedings of the Fourteenth International Conference on Enhanced Safety of Vehicles, Munich, Germany, vol. 1 (1994)
Eriksson, M., Papanikotopoulos, N.: Eye tracking for detection of driver fatigue. In: IEEE Conference on Intelligent Transportation Systems, pp. 314–319 (1997)
Ji, Q., Yang, X.: Real-Time Eye, Gaze, and Face Pose Tracking for Monitoring Driving Vigilance. Elsevier Science Ltd., Amsterdam (2002)
Nakano, T., Sugiyama, K., Mizuno, M., Yamamoto, S.: Blink measurement by image processing and application to warning of driver’s drowsiness in automobiles. IEEE Intelligent Vehicles, 285–290 (1998)
Shih, S.-W., Liu, J.: A novel approach to 3-D gaze tracking using stereo cameras. IEEE Transactions on Systems, Man and Cybernetics 34(1), 234–245 (2004)
Ron, K., Paul, R.: PERCLOS: A Valid Psychophysiological Measure of Alertness by Psychomotor Vigilance, Federal Highway Administration, Office of Motor Carriers, United States (1998)
Nilsson, M., Nordberg, J., Claesson, I.: Face Detection Using Local SMQT Features And Split Up SNoW Classifier. IEEE International Conference on Acoustics, Speech and Signal Processing 2, 589–592 (2007)
Barzilai, R., Himmelblau, C.: Driving Assistance system: Drowsiness Detection by video camera, Department of Electrical Engineering The Vision Research and Image Science Laboratory, Technion - Israel Institute of Technology
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Khan, M.I., Mansoor, A.B. (2008). Real Time Eyes Tracking and Classification for Driver Fatigue Detection. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_72
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DOI: https://doi.org/10.1007/978-3-540-69812-8_72
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