Estimating 3D egomotion from perspective image sequence

The computation of sensor motion from sets of displacement vectors obtained from consecutive pairs of images is discussed. The problem is investigated with emphasis on its application to autonomous robots and land vehicles. The effects of 3D camera rotation and translation upon the observed image are discussed, particularly the concept of the focus of expansion (FOE). It is shown that locating the FOE precisely is difficult when displacement vectors are corrupted by noise and errors. A more robust performance can be achieved by computing a 2D region of possible FOE locations (termed the fuzzy FOE) instead of looking for a single-point FOE. The shape of this FOE region is an explicit indicator of the accuracy of the result. It has been shown elsewhere that given the fuzzy FOE, a number of powerful inferences about the 3D sense structure and motion become possible. Aspects of computing the fuzzy FOE are emphasized, and the performance of a particular algorithm on real motion sequences taken from a moving autonomous land vehicle is shown