Abstract
In this paper, we propose a model-based method of estimating the velocity of a moving object from a series of images. Assuming that the motion is described by an affine transformation, we construct a discrete-time state variable model of the motion based on the dynamic motion imagery modeling technique proposed by Schalkoff. Using this state variable model, we derive an adaptive Kalman filter algorithm to estimate the velocity. Some estimation results are presented to show the effectiveness of the proposed algorithm.
