A sliding mode approach to visual motion estimation

Official URL: http://dx.doi.org/10.1109/AMC.2006.1631751

The problem of estimating motion 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 of a moving body with the aid of a CCD camera. We consider a variety of dynamical systems which arise in machine vision applications and develop a novel identication 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 “equivalent control” to explicitly compute parameters. Much of our analysis has been substantiated by computer simulations and real experiments.