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In some situations, high quality eye tracking systems are not affordable. This generates the demand for inexpensive systems built upon non-specialized, off the shelf devices. Investigations show that algorithms developed for high resolution systems do not perform satisfactorily on such lowcost and low resolution systems. We investigate
algorithms specifically tailored to such low resolution input devices, based on combination of different strategies. An approach called gradient direction consensus is introduced and compared to image based correlation with adaptive templates as well as other known methods. The results are compared using synthetic input data with known ground truth.