1. A method to filter outliers in an image-aided motion-estimation system, the method comprising: removing, from data sent to a RANdom SAmple Consensus (RANSAC) algorithm, which functions as a post-filtering algorithm, data associated with a plurality of bad sets of eight-image-points and two camera positions by: selecting eight-image-points in a first image received from a moving imaging device at at least one processor; selecting eight-image-points in a second image that correspond to the selected eight-image-points in the first image at the at least one processor, the second image being received from the moving imaging device; scaling the selected image-points at the at least one processor so the components of the selected image-points are between two selected values on the order magnitude of 1; building an 8-by-9 matrix (A) from the scaled selected image-points at the at least one processor; determining a condition number for the 8-by-9 matrix at the at least one processor; and rejecting the 8-by-9 matrix built from the selected image-points when the determined condition number is greater than or equal to a condition-number threshold, wherein a rejected 8-by-9 matrix (A) is not used to compute a rotation and a translation to be sent to the RANSAC algorithm; and sending a computed rotation of the imaging device and a computed translation of the imaging device occurring between a first time and a second time, responsive to removing the data associated with the plurality of bad sets of eight-image-points and two camera positions, to the RANSAC algorithm, wherein the RANSAC algorithm obtains a good solution.