Optimal matching of planar models in 3D scenes

The problem of matching a model consisting of the point features of a flat object to point features found in an image that contains the object in an arbitrary three-dimensional pose is addressed. Once three points are matched, it is possible to determine the pose of the object. Assuming bounded sensing error, the author presents a solution to the problem of determining the range of possible locations in the image at which any additional model points may appear. This solution leads to an algorithm for determining the largest possible matching between image and model features that includes this initial hypothesis. The author implements a close approximation to this algorithm, which is O( nm isin;6), where n is the number of image points, m is the number of model points, and isin; is the maximum sensing error. This algorithm is compared to existing methods, and it is shown that it produces more accurate results