Abstract

Modern robotics began with the realization that models must be dynamic (incorporating temporal derivatives of state variables) to be useful in control theory. These advances are now being incorporated into vision, sometimes with spectacular results. In this tutorial I will review the basics of optimal observer theory, its recent successes in vision, and discuss how these ideas can be combined with other "hot" topics such as wavelet transforms and neural networks.

© 1991 Optical Society of America