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A robust method for drowsiness detection using distance and gradient vectors

机译:使用距离和梯度向量进行嗜睡检测的鲁棒方法

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This paper presents a drowsiness detection method for drivers. The drowsiness is detected by monitoring the eye state (open or close). Firstly, the detection of human face and eye regions is performed using the Haar cascade method. We then locate a dark circular object (i.e. the pupil) using two vectors within the eye regions: one is distance vectors and the other gradient vectors. The cross-correlation between these two vectors should be maximized at the center of the dark circle. Experimental results show that the proposed method works well in bright, dim, and dark situations. For the dark situation, we use infrared LEDs to make a face visible. The computation speed of the proposed method is fast enough to perform at video rate.
机译:本文提出了司机的嗜睡检测方法。通过监测眼睛状态(打开或关闭)来检测嗜睡。首先,使用HAAR级联方法进行人脸和眼部区域的检测。然后,我们使用眼部内部的两个向量定位一个暗圆形物体(即,瞳孔):一个是距离矢量和另一个梯度向量。这两个向量之间的互相关应该在暗圈的中心最大化。实验结果表明,该方法在明亮,暗淡和黑暗的情况下运作良好。对于黑暗的情况,我们使用红外LED使脸部可见。所提出的方法的计算速度足以以视频速率执行。

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