Detecting and tracking of 3D face pose for human-robot interaction
Faces play a major role in many HCI systems, because they represent a rich source of information. Being able to estimate the 3D face pose in real-time, we can get a clue about user's intentions or to assess which object become his/her focus of attention. This paper has two main contributions. First, we propose an automatic 3D face pose initialization scheme for our real-time tracker by adopting a 2D face detector and an eigenface system. Second, we use the proposed methods - the initialization and tracking - for controlling the orientation of an AIBO camera. We show how the changes in user's face movement can be imitated by the robot's camera and how it can be applied to map an indoor scene.