Model-based velocity measurement using image processing

In this paper, we propose a model-based method of estimating the velocity of a moving object from a series of images. The proposed method utilizes Kalman filtering technique. 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 a Kalman filter algorithm. Some simulation results are presented to show that the proposed Kalman filter algorithm is superior to a simple least square method without a model.