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System and method for detecting gaze direction

机译:视线方向检测系统及方法

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We try to develop a support application for physically handicapped children to communicate with others by blinks. Fist, we try to detect an eye area by using OpenCv. Then we develop the way to detect opening and closing of eyes. We combine the method using saturation and using complexity of image to get more accurate results to detect blinks. Then we develop the technique into a communication application that has the accurate and high-precision blink determination system to detect letters and put them into sound. Then we applied this highly precise blink detection method to developing the non-contact communication support tool which judges the eye direction from ocular movement. We combine eyes direction and blink to choose a letter. This blink determination and gaze detraction detecting made it possible to choose letters remarkably fast. Furthermore, we digitized blurring of the vibration of the center point of the right and left eyes by the comparison with the afterimage and replaced middle point of the amount of change with scatter diagram and distinguished the state of the subject. We will find association with fatigue degree, sleep shortage and an intensive degree and the blurring of the eyeball vibration of right and left using neural network in future.
机译:我们尝试为残障儿童开发支持应用程序,以便他们眨眼间与他人交流。拳头,我们尝试使用OpenCv检测眼睛区域。然后,我们开发出检测眼睛睁开和闭合的方法。我们结合使用饱和度和图像复杂度的方法来获得更准确的结果来检测眨眼。然后,我们将该技术开发为具有准确,高精度眨眼确定系统的通信应用程序,该系统可以检测字母并将其转换为声音。然后,我们将这种高精度的眨眼检测方法应用于开发非接触式通信支持工具,该工具可根据眼动判断眼睛的方向。我们结合眼睛的方向并眨眼选择一个字母。这种眨眼确定和注视力降低检测使得可以非常快速地选择字母。此外,通过与残像的比较,将左右眼的中心点的振动的模糊化进行了数字化,并用散布图代替了变化量的中点,从而区分了被摄体的状态。将来,我们将使用神经网络发现与疲劳程度,睡眠不足和强度不足以及左右眼球振动的模糊有关。

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