Control of a computer workstation via face position and facial gesturing would be an important advance for people with hand or body disabilities as well as for all users. Steps toward realization of such a system are reported here. A computer system has been developed to track the eyes and the nose of a subject and to compute the direction of the face. Face direction and movement is then used to control the cursor. Test results show that the resulting system is usable, although several improvements are needed.>

Scanning systems of existing range finders are sequential. The understanding and analysis of static range images has spread in the scientific community. Such images are widely used in the fields of vision and robotics. However, it is not yet clear what a range finder sees and what it does not see at high velocities. Depending on the scanning system, obstacles may be missed, if the vehicle velocity is not well related to the acquisition rate. A Laser Range Finder Scanning System Simulator such as LRF3S helps to relate vehicle motion to the scanning mechanism. Simulations show the location of each scanned point on the scene at speeds defined on the trajectory. The authors believe that they help to understand dynamic range images and that they are a framework for the design of a range finder scanning system best adapted for an application.>

Computer operation via face orientation provides a means of communication for people with severe physical disability. The authors present a near-real-time computer system to track the eyes and the nose of a subject and compute the direction of the face. As presented by K. Ohmura et al. (1988), the direction can be computed from three natural feature points extracted from the face. The computational approach taken in this system is motivated by the practical requirements of near-real-time performance and accuracy. The approach is based on the reflection characteristic of the cornea. Any bright light source forms a twinkle in the eye that is fixed as long as the light source is fixed. Face direction detection is treated as a 2D tracking problem. The eye twinkles are extracted from the image and used to locate the nose. A final experiment shows that the face direction obtained from the three feature points is precise enough to control the mouse cursor to make selection from a menu with large light buttons.>