Observer Forms for Perspective Systems

Abstract

Estimation of 3D position information from 2D images in computer vision systems can be formulated as a state estimation problem for a nonlinear perspective dynamic system. The multi-output state estimation problem has been treated by several authors using methods for nonlinear observer design. This paper shows that a perspective system can be transformed to two observer forms, and provides constructive methods for arriving at the transformations. These observer forms lead to straightforward observer designs. First, it is shown that using an output transformation, the system admits an observer form which leads to an observer with linear error dynamics. A second observer design is based on a time scaled block triangular form. Both designs assume a commonly used observability condition. The designs are demonstrated in simulation.