Computer Interface Using Eye Tracking for Handicapped People

  • Eun Yi Kim
  • Se Hyun Park
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4224)


In this paper, a computer interface for handicapped people is proposed, where input signals are given by eye movement of the handicapped people. Eye movement is detected by neural network (NN)-based texture classifier, which enables our system to be not obliged to constrained environment. To be robust the natural motion of a user, we first detect a user’s face using skin-color information, and then detect her or his eyes using neural network (NN)-based texture classifier. After detection of eye movements, the tracking is performed using mean-shift algorithms. We use this eye-tracking system as an interface to control the surrounding system such as audio, TV, light, phone, and so on. The experimental results verify the feasibility and validity of the proposed eye-tracking system to be applicable as an interface for the handicapped people.


Handicapped People Computer Interface Facial Region Search Window Menu Item 
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  1. Kaufman, A.E., Bandopadhay, A.S., Bernard, D.: An Eye Tracking Computer User Interface. In: Proceedings, IEEE Symposium on Research Frontiers in Virtual Reality, pp. 25–26 (1993)Google Scholar
  2. Liu, T., Zhu, S.: Eyes Detection and Tracking based on Entropy in Particle Filter. In: International Conf. on Control and Automation, pp. 1002–1007 (2005)Google Scholar
  3. Yoo, D., Chung, M.J.: Eye-mouse under Large Head Movement for Human-Computer Interface. In: IEEE International Conf. on Robotics and Automation, pp. 237–242 (2004)Google Scholar
  4. Betke, M., Gips, J., Fleming, P.: The Camera Mouse: Visual Tracking of Body Features to Provide Computer Access for People with Severe Disabilities. IEEE Transactions on Neural Systems and Rehabilitation Engineering 10(1), 1–10 (2002)CrossRefGoogle Scholar
  5. Takami, O., Morimoto, K., Ochiai, T., Ishimatsu, T.: Computer Interface to Use Head and Eyeball Movement for Handicapped People. In: IEEE International Conference on Systems, Man and Cybernetics, pp. 1119–1123 (1995)Google Scholar
  6. Lin, C., Huan, C., Chan, C., Yeh, M., Chiu, C.: Design of a Computer Game using an Eye-tracking Device for Eye’s Activity Rehabilitation. Optics and Lasers in Engineering 42, 91–108 (2004)CrossRefGoogle Scholar
  7. Kim, K.I., Jung, K.: Texture-based Approach for Text Detection in Images using Support Vector Machines and Continuously Adaptive Mean Shift Algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(12), 1631–1639 (2003)CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Eun Yi Kim
    • 1
  • Se Hyun Park
    • 2
  1. 1.Department of Internet and Multimedia EngineeringKonkuk Univ.Korea
  2. 2.School of Computer and CommunicationDaegu Univ.Korea

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