Visual motion and structure estimation using sliding mode observers
The problem of estimating motion and structure from a sequence of images has been a major research theme in machine vision for many years and remains one of the most challenging ones. In this work, we use sliding mode observers to estimate the motion and the structure of a moving body with the aid of a change-coupled device (CCD) camera. We consider a variety of dynamical systems which arise in machine vision applications and develop a novel identification procedure for the estimation of both constant and time-varying parameters. The basic procedure introduced for parameter estimation is to recast image feature dynamics linearly in terms of unknown parameters and construct a sliding mode observer to produce asymptotically correct estimates of the observed image features, and then use the observer input to compute parameters. Much of our analysis has been substantiated by computer simulations and real experiments.