Accession Number : ADA294535

Title :   An Abstract Representation For Model-Based Computer Vision.

Descriptive Note : Doctoral thesis,

Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH

Personal Author(s) : Banks, Sheila B.

PDF Url : ADA294535

Report Date : MAY 1995

Pagination or Media Count : 127

Abstract : The current work presented is research into a general and flexible representation technique for model based computer vision. This abstract representation integrates various sources of knowledge within model based vision: functional, geometric, and relational; and provides a representation to express image data, image extracted parameters, and model parameters. The abstract representation is based upon the notion of feature structures as derived from linguistic applications of unification grammars and the manipulation technique of unification. The representation of feature structures and the manipulation technique of unification are combined into a lattice structure that is partially ordered by the subsumption relationship. These aspects are explored as the backbone of the abstract representation of the unification grammar application to model based computer vision. Promising aspects of accomplishing parallel unification and unifying solution search lattices in parallel are discussed. An evaluation of the major results of this work and a discussion on areas for future research conclude this dissertation.

Descriptors :   *COMPUTER VISION, MATHEMATICAL MODELS, PARAMETERS, THESES, OPTICAL IMAGES, ABSTRACTS, EXTRACTION, ARTIFICIAL INTELLIGENCE, GRAMMARS.

Subject Categories : Bionics

Distribution Statement : APPROVED FOR PUBLIC RELEASE