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Depth computation in robotics is an important step towards providing robust and accurate navigation capabilities to a mobile robot. In this paper we examine the problem of depth estimation with the view to be used in parsimonious systems where fast and accurate measurements are critical. For this purpose we have combined two methods, namely optical flow and least squares in order to infer depth estimates between a robot and a landmark. In the optical flow method the variation of the optical flow vector at varying distances and velocities is observed. In the least squares method snapshots of a landmark are taken from different robot positions. The results of the two methods show that there is a significant increase in depth estimation accuracy by combining optical flow and least squares.