지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
이용수
초록· 키워드
오류제보하기
Objective: The aim of this study is to classify between intentional and natural blinks in vision based eye tracking system. Through implementing the classification method, we expect that the great eye tracking method will be designed which will perform well both navigation and selection interactions. Background: Currently, eye tracking is widely used in order to increase immersion and interest of user by supporting natural user interface. Even though conventional eye tracking system is well focused on navigation interaction by tracking pupil movement, there is no breakthrough selection interaction method. Method: To determine classification threshold between intentional and natural blinks, we performed experiment by capturing eye images including intentional and natural blinks from 12 subjects. By analyzing successive eye images, two features such as eye closed duration and pupil size variation after eye open were collected. Then, the classification threshold was determined by performing SVM(Support Vector Machine) training. Results: Experimental results showed that the average detection accuracy of intentional blinks was 97.4% in wearable eye tracking system environments. Also, the detecting accuracy in non-wearable camera environment was 92.9% on the basis of the above used SVM classifier. Conclusion: By combining two features using SVM, we could implement the accurate selection interaction method in vision based eye tracking system. Application: The results of this research might help to improve efficiency and usability of vision based eye tracking method by supporting reliable selection interaction scheme.
목차
ABSTRACT
1. Introduction
2. Method
3. Results
4. Discussion
5. Conclusion
Acknowledgements
References
참고문헌 (20)
참고문헌 신청
Agostino, R. / 2008 / Voluntary, spontaneous, and reflex blinking in parkinson's disease / Movement Disorders 23(5):669~675
Al-Haddad, A. / 2011 / Gaze at desired destination, and wheelchair will navigate towards it. new technique to guide wheelchair motion based on EOG signals / Informatics and Computational Intelligence(ICI) First International Conference :126~131
Berman, B. D. / 2011 / Neural correlates of blink suppression and the buildup of a natural bodily urge / NeuroImage 59(2):1441~1450
Chen, Y. / 2004 / A human-robot interface based on electrooculography / Robotics and Automation(ICRA'04) IEEE International Conference :243~248
Chang, Chih-Chung / 2011 / LIBSVM: a library for support vector machines / ACM Transactions on Intelligent Systems and Technology 2(3):1~27
Al-Haddad, A. / 2011 / Gaze at desired destination, and wheelchair will navigate towards it. new technique to guide wheelchair motion based on EOG signals / Informatics and Computational Intelligence(ICI) First International Conference :126~131
Berman, B. D. / 2011 / Neural correlates of blink suppression and the buildup of a natural bodily urge / NeuroImage 59(2):1441~1450
Chen, Y. / 2004 / A human-robot interface based on electrooculography / Robotics and Automation(ICRA'04) IEEE International Conference :243~248
Chang, Chih-Chung / 2011 / LIBSVM: a library for support vector machines / ACM Transactions on Intelligent Systems and Technology 2(3):1~27
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UCI(KEPA) : I410-ECN-0101-2013-530-003391459