摘要
瞳孔定位作为头戴式视线跟踪系统的核心模块之一,影响着系统的精度和稳定性,但眼球在正常转动中会发生着眼睑遮挡瞳孔问题.针对该问题,提出了一种两级瞳孔定位算法.第一级采用改进的星射线法提取瞳孔边缘轮廓.接着根据3D眼球模型和瞳孔位置提前判断是否存在眼睑遮挡情况,如果不存在,则定位结束,否则进行第二级定位.第二级采用改进的椭圆模板匹配算法,不同于其他椭圆匹配算法,该算法利用3D眼球模型的参数提前获取椭圆的长短轴比例和旋转角度,将匹配的空间复杂度由5维降为3维,提高了匹配的效率.在眼睑遮挡情况下该算法精确检测出瞳孔,并且定位速度较快.
As a key part of the head-mounted eye tracking system, pupil detection not only affects system accuracy, but also system stability. However, the problem of eyelid occlusions arises when eyeball moves. To solve this problem, a Two-Level pupil detection method was proposed. The first level utilizes the improved starburst method to extract pupil edge points and then check whether the pupil is shaded by eyelid. If it＇s not the case, pupil detection ends, otherwise the second level detection is conducted. In the second level detection, improved ellipse template matching method is applied. Unlike other ellipse matching methods, this method is based on a 3D eyeball model. With eyeball parameters, this method estimates ellipse minor-major axis rate and angle of rotation in advance, and then decreases the spatial complexity from five dimensions to three, thus improving matching efficiency. With our method, the pupil can be easily rapidly detected under eyelid occlusions.
基金
国家自然科学基金委-广东省联合基金重点项目(U0835002)资助
