The use of hierarchical models for vertically-integrated scene interpretation is closely related to syntactic recognition, but avoids earlier problems associated with feature definition and extraction.
Recognition is achieved in highly cluttered environments.
Our first work in this area concentrated on specific algorithms for specific object recognition problems. Current foundational work is much broader, not concentrating on specific algorithms for specific applications, yet building on what we have learned from the early algorithm development efforts. The current effort is referred to as the compositional approach to vision. We propose to develop a framework for machine vision based upon the idea of composition. The restricted composition rules amount to an explicit formulation of contextual constraints.