3D 3D 人类-机器人眼接触的 " 考虑 " 头目 " 对第一人的观点的 " 头点预测 " 。 (3D Head-Position Prediction in First-Person View by Considering Head Pose for Human-Robot Eye Contact)

For a humanoid robot to make eye contact to initiate communication with a human, it is necessary to estimate the human's head position.However, eye contact becomes difficult due to the mechanical delay of the robot while the subject with whom the robot is interacting with is moving. Owing to these issues, it is important to perform head-position prediction to mitigate the effect of the delay in the robot's motion. Based on the fact that humans turn their heads before changing direction while walking, we hypothesized that the accuracy of three-dimensional(3D) head-position prediction from the first-person view can be improved by considering the head pose into account.We compared our method with the conventional Kalman filter-based method, and found our method to be more accurate. The experimental results show that considering the head pose helps improve the accuracy of 3D head-position prediction.

翻译：为了让人形机器人进行眼神接触,以便与人进行交流,有必要估计人的头部位置。然而,由于机器人与机器人互动的主体移动时机械的延迟,眼部接触变得很困难。由于这些问题,必须进行头部位置预测,以减轻机器人运动延迟的影响。基于人类在走路时在改变方向之前转头这一事实,我们假设,如果考虑到头部姿势,从第一人的角度对三维(3D)头部位置预测的准确性可以提高。我们比较了我们的方法和传统的Kalman过滤法,发现我们的方法更准确。实验结果表明,考虑头部姿势会帮助提高3D头部姿势预测的准确性。