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Teaching Assistant System used Eye Tracking Device Based on Gaze Estimation by Neural Network and Intention Recognition by Fuzzy Inference

机译:基于神经网络注视和模糊推理意识识别的眼动追踪装置教学辅助系统

摘要

Intention recognition can use multiple factors as inputs such as gestures, face images and eye gaze position. On the other hand,eye tracking technology,with its special advantages of applying to Human-Computer Interaction (HCI),can be utilized to develop assistant systems for people with mobility difficulties. In this paper, we propose gaze estimation position information as input of fuzzy inference to achieve intention recognition based on object recongition and construct an assistant system by using humanoid robot. Our approach is divided into three parts: user's gaze estimation, intention recognition and behavior execution. In gaze estimation part, differing from the previous studies, neural network has been used as the decision making unit, and then gaze position on computer screen is estimated. In intention recognition part, user intention is recognized by using gaze frequency and continuous gaze staying time as input of fuzzy inference after an initial intention region set has been found. At last, by using an autonomous humanoid robot, experiments are performed based on the result of intention recognition. after confirmed by user, the robot was controlled with and assistant task for user precisely.
机译:意图识别可以使用多种因素作为输入,例如手势,面部图像和视线位置。另一方面,眼动追踪技术以其在人机交互(HCI)中的特殊优势,可用于为行动不便的人开发辅助系统。本文提出了凝视估计位置信息作为模糊推理的输入,以实现基于物体识别的意图识别,并利用人形机器人构建了辅助系统。我们的方法分为三个部分:用户的凝视估计,意图识别和行为执行。在注视估计部分,与以前的研究不同,神经网络已被用作决策单元,然后在计算机屏幕上估计注视位置。在意图识别部分中,在找到初始意图区域集之后,通过使用凝视频率和连续凝视停留时间作为模糊推断的输入来识别用户意图。最后,使用自主的人形机器人,基于意图识别的结果进行实验。在用户确认后,该机器人由用户精确控制并执行辅助任务。

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