A novel visual interface for human-robot communication

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Abstract
The purpose of a robot is to execute tasks for people. People should be able to communicate with robots in a natural way. People naturally express themselves through body language using facial gestures and expressions. We have built a human-robot interface based on head gestures for use in robot applications. Our interface can track a person's facial features in real time (30 Hz video frame rate). No special illumination or facial makeup is needed to achieve robust tracking. We use dedicated vision hardware based on correlation image matching to implement the face tracking. Tracking using correlation matching suffers from the problems of changing shade and deformation or even disappearance of facial features. By using multiple Kalman filters we are able to overcome these problems. Our system can accurately predict and robustly track the positions of facial features despite disturbances and rapid movements of the head (including both translational and rotational motion). Since we can reliably track faces in real-time we are also able to recognize motion gestures of the face. Our system can recognize a large set of gestures (15) ranging from yes, no and may be to detecting winks, blinks and sleeping. We have used an approach that decomposes each gesture into a set of atomic actions, e.g. a nod for yes consists of an atomic up followed by a down motion. Our system can understand gestures by monitoring the transition between atomic actions.

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