基于由粗到精定位的列车驾驶员瞳孔和眼角点检测

Detection of Train Driver’s Pupil and Eye Corner Based on Coarse to Fine Positioning

提出一种由粗到精定位的列车驾驶员瞳孔和眼角点检测方法,采用基于监督下降法的面部特征点定位和跟踪技术对驾驶员的眼角点进行粗定位,在面部特征点正确定位的基础上根据相应点的位置获取眼睛图像。采用圆形模板求得眼睛图像中每个像素点的灰度比率,并将其作为权值获取积分投影曲线,对瞳孔点粗定位。将已检测到的瞳孔中心点和眼角点作为初始点,采用基于局部二值特征的定位技术对眼角点和瞳孔位置进行精确定位。利用视频和图像数据库进行实验测试,实验结果表明:提出的方法能够有效定位驾驶员眼角点和瞳孔位置,其瞳孔检测精度优于最新提出的方法。

This paper proposed a train driver’s pupil and eye corner detection method based on coarse to fine positioning. First, a facial landmark positioning and tracking technology based on supervised descent method was used to roughly locate the eye corners of drivers, and extract eye images based on the position of corresponding points resulted from the correct location of facial feature points. Then, a circular sliding template was used to traverse the eye image to obtain the gray ratio of each pixel, and a weighted integral projection method was used to detect the pupils, roughly. Finally, the detected landmarks on eye corners and pupils were adopted as the initial points, and a location technology based on local binary feature was used to precisely locate the position of the pupils and eyes corners. Image and video datasets were adopted to evaluate the proposed method. The experimental results show that this algorithm can effectively locate the position of the pupils and eye corners of drivers and outperforms other state-of-the-art methods for pupil detection.