A fully automatic system for human detection and tracking in front of an Interactive Whiteboard is presented. When a
person is between a projector and the projection area, deleterious effects can be created from light shining on the face.
We developed a stereo vision system that can be used to mitigate problems arising from this issue by accurately
detecting the human body and masking the face. We present two main parts of this system: namely, automatic system
calibration and the human detection and tracking. We use a checkerboard pattern that is projected on the whiteboard at
start-up for automatic calibration. Grid patterns from two images are processed, and points between them are detected
and localized. A projective transform is used to set the homography between the two images. Testing shows precise
automatic calibration, with an average RMS error of 0.4 pixels in the off-line test. Human detection and tracking is
accomplished using a similarity measure, foreground segmentation, principle component analysis, body shape feature
extraction, disparity measure, and location estimation. We achieved an average detection rate of 97.7 % in the off-line
tests. The method was fully implemented in a real-time system and testing showed the system to be very robust.
Human computer interaction is an active area of research that focuses on how humans can better work with machines. In order for this to happen, there must be an enabling technology that creates a natural interface between man and machine. In this paper an enabling technology in the form of a camera based man-machine interface is described. This system uses smart cameras to analyze a scene directly in front of a computer display. The analysis determines where a user has touched the display and then treats that information is a mouse click thereby allowing the computer to be controlled. There are significant technological problems that have been overcome in order to make the system robust enough for commercialization. System architecture and operation is described and some interesting advantages of using machine vision are presented. The interface is also shown to be compatible with very large computer displays thus creating a very natural interface with familiar usage paradigms.