视线追踪中一种新的由粗及精的瞳孔定位方法

A new pupil localization method from rough to precise in gaze tracking

  • 摘要: 基于图像处理的方法,采用了由粗及精的瞳孔定位思想,提出了一种高精度的瞳孔定位算法。该算法首先利用瞳孔区域的直方图,采用改进的最大类间方差法自适应地分割瞳孔区域,实现粗略定位,然后利用瞳孔灰度的梯度特性来精确定位瞳孔边缘点,最后在像素级瞳孔边缘点的基础上,采用亚像素定位方法,更精确地求得亚像素级瞳孔边缘点,并通过椭圆拟合的方法来精确确定瞳孔的中心位置。另外,针对瞳孔被遮挡的情况,本文提出了一种等距离补偿瞳孔的方法。多次实验结果证明了该算法对遮挡瞳孔的定位有较强的鲁棒性,可以准确地定位瞳孔的位置。

     

    Abstract: The gaze tracking technology is widely used in many fields, and it has a broad application prospect in the field of human-computer interaction. The technology is based on the eye characteristic parameters and the gaze parameters, and it estimates the direction of sight and placement of sight based on the eye model. Therefore, accurately locating the pupil position is important in the gaze tracking technology, and it directly affects the accuracy of the gaze tracking result. Presently, there are numerous algorithms used in eye detection; however, most of them are characterized by some problems, such as the low accuracy of locating the pupil position, high detection error, and slow operation speed; thus, they cannot meet the accuracy requirements of locating the pupil position. To solve these problems, in this study, a concept of pupil localization method from rough to precise was adopted, and a high-accuracy pupil localization method based on image processing was proposed. In this method, first, the improved maximal between-cluster variance algorithm used the histogram of the pupil region to adaptively segment region to roughly locate the pupil region. Then the pupil edge points can be accurately located by the gradient of the pupil grayscale. Finally, a sub-pixel localization method was adopted on the basis of the pixel level edge points of the pupil to locate the sub-pixel level edge points of pupil more accurately, and the center position of the pupil was accurately determined by the method of ellipse fitting. In addition, an equidistance pupil compensation method was proposed in this paper for the situation of pupil occlusion. Several experimental results show that the algorithm is robust to locate the position of pupil occlusion and that it can achieve accurate pupil localization.

     

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