Eye-based Interaction Using Embedded Optical Sensors on an Eyewear Device for Facial Expression Recognition

Katsutoshi Masai, K. Kunze, M. Sugimoto
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引用次数: 11

Abstract

Non-verbal information is essential to understand intentions and emotions and to facilitate social interaction between humans and between humans and computers. One reliable source of such information is the eyes. We investigated the eye-based interaction (recognizing eye gestures or eye movements) using an eyewear device for facial expression recognition. The device incorporates 16 low-cost optical sensors. The system allows hands-free interaction in many situations. Using the device, we evaluated three eye-based interactions. First, we evaluated the accuracy of detecting the gestures with nine participants. The average accuracy of detecting seven different eye gestures is 89.1% with user-dependent training. We used dynamic time warping (DTW) for gesture recognition. Second, we evaluated the accuracy of eye gaze position estimation with five users holding a neutral face. The system showed potential to track the approximate direction of the eyes, with higher accuracy in detecting position y than x. Finally, we did a feasibility study of one user reading jokes while wearing the device. The system was capable of analyzing facial expressions and eye movements in daily contexts.
基于眼交互的嵌入式光学传感器眼镜设备面部表情识别
非语言信息对于理解意图和情感以及促进人与人之间以及人与计算机之间的社会互动至关重要。这些信息的一个可靠来源就是眼睛。我们使用一种用于面部表情识别的眼镜装置来研究基于眼睛的互动(识别眼睛手势或眼球运动)。该设备包含16个低成本光学传感器。该系统允许在许多情况下进行免提交互。使用该设备,我们评估了三种基于眼睛的互动。首先,我们用9个参与者来评估检测手势的准确性。在用户依赖训练下,检测七种不同眼睛手势的平均准确率为89.1%。我们使用动态时间扭曲(DTW)进行手势识别。其次,我们评估了5个用户持有中性面孔时眼睛注视位置估计的准确性。该系统显示出跟踪眼睛大致方向的潜力,在检测位置y方面的准确率高于检测位置x。最后,我们对一个用户戴着该设备阅读笑话进行了可行性研究。该系统能够分析日常环境中的面部表情和眼球运动。
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