Using Logic in a Model-Based Approach to Object Recognition.

Abstract

A model-based object recognition system, predicted on logic as a method of modeling, describing and identifying objects, is proposed. Users supply the object recognition system with models of known object classes in the form of production rules. The system describes each instance of an object found within an image scene as a collection of facts. The modeled rules act upon these facts in a Prolog environment to obtain an interpretation of the original image scene. Since users supply the object models and the Prolog environment supplies the interference mechanism for interpretation, the primary task of the object recognition system is the description process. For each object instance identified within the image scene, declarative statements are formulated which represent observer components, features or attributes of that object. The description of an object instance is restricted to its geometric components which are derived from a skeleton or stick-figure representation of a 2-D silhouette portrayal of an object found in the original image scene. Therefore, object classifications can be modeled in a general way so that the size and orientation of the object is independent of that model.

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1991
Accession Number
ADA244188

Entities

People

  • Michael A. Gennert
  • Suzanne G. Dunn

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Computer Vision
  • Environment
  • Image Recognition
  • Object Recognition
  • Recognition
  • Robotics
  • Two Dimensional
  • Visual Servoing

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computer Vision.