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In this paper, a method to mimic a human face and eyes is proposed which canbe regarded as a combination of computer vision techniques and neural networkconcepts. From a mechanical standpoint, a 3-DOF spherical parallel robot isused which imitates the human head movement. In what concerns eye movement, a2-DOF mechanism is attached to the end-effector of the 3-DOF spherical parallelmechanism. In order to have robust and reliable results for the imitation,meaningful information should be extracted from the face mesh for obtaining thepose of a face, i.e., the roll, yaw, and pitch angles. To this end, two methodsare proposed where each of them has its own pros and cons. The first methodconsists in resorting to the so-called Mediapipe library which is a machinelearning solution for high-fidelity body pose tracking, introduced by Google.As the second method, a model is trained by a linear regression model for agathered dataset of face pictures in different poses. In addition, a 3-DOFAgile Eye parallel robot is utilized to show the ability of this robot to beused as a system which is similar to a human head for performing a 3-DOFrotational motion pattern. Furthermore, a 3D printed face and a 2-DOF eyemechanism are fabricated to display the whole system more stylish way.Experimental tests, which are done based on a ROS platform, demonstrate theeffectiveness of the proposed methods for tracking the human head and eyemovement.

Experimental Study on the Imitation of the Human Head-and-Eye Pose Using the 3-DOF Agile Eye Parallel Robot with ROS and Mediapipe Framework