Single camera based motion and shape estimation using extended Kalman filtering

The problem of estimating motion and shape of a moving object has been cons idered from a time series of image data obtained via perspective projection . First of all, we analyze motion and shape dynamics of a planar surface un dergoing rigid motion. It is shown that, for a class of motion parameters, the shape parameters are asymptotically decoupled from the optical flow dyn amics, hence, become unobservable, asymptotically. For other choices of mot ion parameters, shape parameters remain asymptotically observable. We prese nt a numerical study and compare a recursive algorithm using an extended Ka lman filter with a nonrecursive algebraic method, for estimating motion and planar surface parameters. The conclusion of the paper is that recursive m ethods yield robust estimates whenever they are applicable. Algebraic estim ation schemes, on the other hand, are always susceptible to noise. (C) 2001 Elsevier Science Ltd. All rights reserved.