首页|Fatigue recognition in E-learning based on eye tracking and detection
Fatigue recognition in E-learning based on eye tracking and detection
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NETL
A learning fatigue recognition method based on eye tracking and detection is proposed when E-learners regular appeared physical or psychological fatigue state。 An inner eye corner filter was used to locate the positions of inner eye corner accurately。 The eye was tracked in real time by detecting the inner eye corner。 Open eye template could be created online and dynamically updated。 The opening or shutting of eyes could be recognized using correlation with an online open eye template。 Experimental results indicate that the proposed algorithm can locate the positions of inner eye corner with an accuracy rate of more than 98%。 An accuracy rate of 97。5% in blink detection is obtained using the proposed method at a processing rate of 50 fields per second。
E-learningeye trackingfigure detection
Xikun Zhang、Jie Hou
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Tianjin University, college of precision instrument and opto-electronics engineering, Tianjin University, China
Hangzhou(CN)
2011 International Conference on Multimedia Technology
NETL
