Recognition of human head orientation based on artificial neural networks

Humans easily recognize where another person is looking and often use this information for interspeaker coordination. We present a method based on three neural networks of the local linear map type which enables a computer to identify the head orientation of a user by learning from examples. One network is used for color segmentation, a second for localization of the face, and the third for the final recognition of the head orientation. The system works at a frame rate of one image per second on a common workstation, We analyze the accuracy achieved at different processing steps and discuss the usability of the approach in the context of a visual human-machine interface.