Issue No. 11 - November (1990 vol. 12)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.61704
<p>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.</p>
motion estimation; camera translation; FOE location; 3D egomotion; perspective image sequence; sensor motion; displacement vectors; autonomous robots; land vehicles; 3D camera rotation; focus of expansion; noise; errors; fuzzy FOE; mobile robots; pattern recognition; picture processing; vehicles
W. Burger and B. Bhanu, "Estimating 3D Egomotion from Perspective Image Sequence," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 12, no. , pp. 1040-1058, 1990.