Issues in extracting motion parameters and depth from approximate translational motion

In dynamic situations where the sensor is undergoing primarily translational motion with a relatively small rotational components, it might seem likely that approximate translational motion algorithms can be effective. It is shown quantitatively, however, that even small rotations can significantly affect the computation of the focus of expansion (FOE). This is shown theoretically for the case in which the environment is a frontal plane, and also experimentally. Two algorithms are presented. One is an existing general motion algorithm. The second is a pure translational algorithm based on the weighted Hough transform. The depth results obtained using the second algorithm are reasonable, although they are not as good as those using general motion