A fast method for estimating the uncertainty in the location of image points in 3D recognition

Efficient and robust model-based recognition systems need to be able to estimate reliably and quickly the possible locations of other model features in the image when a match of several model points to image points is given. Errors in the sensed data lead to uncertainty in the computed pose of the object which in turn lead to uncertainty in those positions. We present a very fast and accurate method for estimating these uncertainty regions. Our basic method deals with an initial match of three points and is extended using statistical methods to estimate the uncertainty region using initial matches of any size.