基于双目相机的眼动仪头部姿态估计方法

Head Pose Estimation Method of Eye Tracker Based on Binocular Camera

头部姿态估计是视线追踪的重要组成部分,但相关研究大多利用人脸的二维(2D)图像进行计算,因此,提出了一种基于双目相机的眼动仪三维(3D)头部姿态估计方法。首先,建立空间坐标系与人脸本征坐标系;然后,利用Dlib库检测双目图像的人脸特征点,并求取对应特征点的视差及3D坐标;最后,结合人脸对称性计算3D头部姿态的欧拉角,并提出了一种俯仰角修正算法。为了验证本方法的精确性,利用模特人头和高精度光学仪器构建了双目头部姿态数据集。实验结果表明,本方法测量欧拉角的平均误差为1.08°,均方根误差为1.25。相比基于2D图像的OpenFace方法,本方法的精度更高、鲁棒性更强。

Head pose estimation is an important part of gaze tracking but is usually calculated from two-dimensional(2D)images of human faces in most studies.Therefore,athree-dimensional(3D)head pose estimation method of eye tracker based on binocular camera is proposed in this paper.First,the spatial coordinate system and the facial intrinsic coordinate system are established.Then,the facial landmarks of the binocular image are detected by referencing the Dlib and the disparity and 3D coordinates of the corresponding facial landmarks are calculated.Finally,the Euler angle of the 3D head pose is calculated based on the symmetry of the face,and a pitch-angle correction algorithm is applied.To verify the accuracy of the method,a binocular head pose dataset is constructed using model heads and high-precision optical instruments.The experimental results show that the average error of the Euler angle by the method is 1.08°and the root mean square error is 1.25.The accuracy and robustness of the method exceeded those of the OpenFace method based on 2D images.