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Deep learning for three dimensional (3D) gaze prediction

机译:三维凝视预测的深度学习

摘要

There is disclosed a computer implemented eye tracking system and corresponding method and computer readable storage medium, for detecting three dimensional, 3D, gaze, by obtaining at least one head pose parameter using a head pose prediction algorithm, the head pose parameter(s) comprising one or more of a head position, pitch, yaw, or roll; and to input the at least one head pose parameter along with at least one image of a user's eye, generated from a 2D image captured using an image sensor associated with the eye tracking system, into a neural network configured to generate 3D gaze information based on the at least one head pose parameter and the at least one eye image.
机译:本发明公开了一种计算机实现的眼睛跟踪系统及相应方法和计算机可读存储介质,用于通过使用头部姿势预测算法获得至少一个头部姿势参数来检测三维、3D、凝视,头部姿势参数包括头部位置、俯仰、偏航或滚动中的一个或多个;以及将所述至少一个头部姿势参数以及从使用与所述眼睛跟踪系统相关联的图像传感器捕获的2D图像生成的用户眼睛的至少一个图像输入到神经网络中,所述神经网络被配置为基于所述至少一个头部姿势参数和所述至少一个眼睛图像生成3D凝视信息。

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