Iterative pose estimation using coplanar feature points

This paper presents a new method for the computation of the position and orientation of a camera with respect to a known object, using four or more coplanar feature points. Starting with the scaled orthographic projection approximation, this method iteratively refines up to two different pose estimates, and provides an associated quality measure for each pose. When the camera distance is large compared with the object depth, or when the accuracy of feature point extraction is low because of image noise, the quality measures for the two poses are similar, and the two pose estimates are plausible interpretations of the available information. In contrast, known methods using a closed form pose solution for four coplanar points are not robust for distant objects in the presence of image noise because they provide only one of the two possible poses and may choose the wrong pose. (C) 1996 Academic Press, Inc.