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A 3D gaze estimation method based on facial feature tracking

机译:基于面部特征跟踪的3D凝视估计方法

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A 3D gaze estimation and tracking algorithm based on facial feature tracking is present in this paper. By using two cameras, 2D facial feature points are detected and tracked with Active Shape Models (ASM). Then, the 3D coordinates of the feature points on a face can be obtained by stereo vision. The full 3D pose of head is obtained by comparing the feature points of current pose with initial head pose. The head pose estimation eliminate the restraint of head movement. Based on a 3D eye model with facial feature points, 3D visual axis can be obtained by estimating the 3D pupil center and head pose after a one-time personal calibration. The experimental results show the accuracy of our gaze tracking system achieves less than 3 degree.
机译:本文存在基于面部特征跟踪的3D凝视估计和跟踪算法。通过使用两个相机,使用主动形状模型(ASM)检测和跟踪2D面部特征点。然后,可以通过立体视觉获得面部上的特征点的3D坐标。通过将当前姿势的特征点与初始头部姿势进行比较来获得头部的完整3D姿势。头部姿势估计消除了头部运动的束缚。基于带有面部特征点的3D眼模型,通过在一次性个人校准之后估计3D光瞳中心和头部姿势,可以获得3D视力。实验结果表明,我们的注视跟踪系统的准确性达到3度。

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