Human-Computer Interaction Behavior and Intention Prediction Model Based on Eye Movement Characteristics
LIANG Yong-qiang1, WANG Wei1, QU Jue1,2, YANG Jie1, LIU Xiao-wei1
1. Air and Missile Defense College, Air Force Engineering University. Xi'an, Shaanxi 710051, China;
2. School of Aeronautics, Northwestern Polytechnical University. Xi'an, Shaanxi 710072, China
Abstract：Aiming at the demand of predicting adaptive interface user's intention,This paper presents a method of human-computer interaction behavior classification and intention prediction based on eye movement characteristics.By establishing a simplified interface model,the user's operating behavior is divided into 5 categories,design visual interaction experiment to collect the relevant states' eye movement data.The SVM(Support Vector Machine) algorithm is used to establish the classification prediction model,combined with the difference analysis method to select the eye movement feature component.Finally,the position X coordinate,the position Y coordinate,the gaze time,the eye jump amplitude and the pupil diameter of the 3 consecutive sampling fixation points can be used as the characteristic parameters to obtain the better prediction effect,and the prediction accuracy can reach more than 90%.
梁永强, 王崴, 瞿珏, 杨洁, 刘晓卫. 基于眼动特征的人机交互行为意图预测模型[J]. 电子学报, 2018, 46(12): 2993-3001.
LIANG Yong-qiang, WANG Wei, QU Jue, YANG Jie, LIU Xiao-wei. Human-Computer Interaction Behavior and Intention Prediction Model Based on Eye Movement Characteristics. Acta Electronica Sinica, 2018, 46(12): 2993-3001.
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2018, Vol. 46 
