Towards the Automatic Generation of Recognition Strategies

Abstract

This paper describes a method for the automatic generation of recognition strategies. This is accomplished using a technique developed for quantifying the following properties of 3-D features which compose models used in 3-D computer vision: robustness, completeness, consistency, cost, and uniqueness. By utilizing this inforniation, the automatic synthesis of a specialized recognition scheme, called a Strategy Tree, is accomplished. Strategy Trees describe, in a systematic and robust manner, the search process used for recognition and localization of particular objects in the given scene. System constraints are satisfied which lead to a set of features which guide the recognition process. Each feature has a Corroborating Evidence Subtrees which validate the initial hypothesis. Verification techniques, used to substantiate or refute these hypotheses, are explored. Experiments are presented.