Real-time tracking of people using stereo and motion

Abstract
Depth and motion measurements from images have a variety of industrial and non-industrial applications. Underlying these two measurement modalities is the ability to accurately and reliably correlate portions of images separated in space, as in the case of a stereo pair, or time, as in the case of a motion sequence. We have developed a unique correlation algorithm as well as special hardware accelerators to allow it to operate at video frame rate. The ability to make measurements in real time is invaluable in observing algorithm performance on dynamic scenes; real-time feedback has also allowed us to apply these low-level measurements in unique ways to several perceptual tasks. In this paper, we describe our progress in the areas of figure-ground separation and active object tracking using our correlation techniques. We illustrate the use of these capabilities to drive an active camera head and a robot vehicle in person-following demonstrations.