A method for reconstructing motion from sequences of tagged magnetic resonance (MR) images is presented. MR tagging is used to create a spatial pattern of varying magnetization so that objects which may otherwise have constant intensity are textured, which reduces the motion ambiguity associated with the aperture problem in computer vision. To compensate for the decay of the tag pattern, a new optical flow algorithm is developed and implemented. The resulting estimated velocity field is then used to recursively update the implied motion reference map over time, thereby tracking the motion of individual particles. If a segmentation of the object is known at the time the tag pattern is created, then an object may be selectively tracked, using the estimated reference map to update the object's position as time progresses. Results are shown for both simulated and actual MR phantom data.