Geometric hashing with attributed features

Geometric hashing systems for object recognition have typically made use of point features in order to describe models and objects. When lines have been included as primitive features, they have been used to generate collections of points from pairwise intersections. In the experiments described in the paper, the authors use line features that include location and orientation information. These features, for which the orientation information is an attribute, are incorporated into a geometric hashing system using weighted voting in order to effect a Bayesian-based maximum likelihood object recognition system. The authors show results of this system which is the first example of the use of attributed features (features with more than coordinate position information) in a geometric hashing application