A recursive estimation of depth from a sequence of images is proposed. Using the spherical projection, a simple equation is derived that relates image motion with the object motion. This equation is reformulated into a dynamical state space model for which Kalman filter can be easily applied to yield the estimate of depth. Point correspondences have been used to obtain feature points and the motion parameters are assumed to be known. The results are illustrated on a real object.
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