Tagged magnetic resonance imaging (MRI) has shown great promise in non-invasive analysis of heart motion. To replace implanted markers as a gold standard, however, tagged MRI must be able to track a sparse set of material points, so-called material markers, with high accuracy. This paper presents a new method for generating accurate motion estimates over a sparse set of material points using standard, parallel-tagged MR images. Each tracked point is located at the intersection of three tag surfaces, each of which is estimated using a thin-plate spline. The intersections are determined by an iterative alternating projections algorithm for which a proof of convergence is provided. The resulting data sets are compatible with applications developed to exploit implanted marker data. One set of these material markers from a normal human volunteer is examined in detail using several methods to visualize the markers. Numerical results that include additional studies are also discussed. Finally, an error analysis is presented using a computer-simulated left ventricle for which material markers are tracked with an RMS error of approximately 0.2 mm for typical imaging parameters and noise levels.