  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.
