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We propose a temporal modeling approach for determining image motion from a sequence of images within which the inherent motion is periodic. To exploit the periodic nature of the motion, we use a Fourier harmonic representation to model the motion field for the entire sequence. We then determine the motion field by estimating the parameters of this representation model. This joint estimation approach can take advantage of the statistics of all the available data in the image sequence. In our experiments, we applied the proposed approach to estimate the cardiac motion in gated cardiac SPECT perfusion images. Our results demonstrate that it could achieve robust estimation in the presence of strong imaging noise.