An Approach to Object Recognition: Aligning Pictorial Descriptions.

Abstract

This paper examines the problem of shape-based object recognition, and proposes a new approach, the alignment of pictorial descriptions. The first part of the paper reviews general approaches to visual object recognition, and divides these approaches into three broad classes; invariant properties methods, object decomposition methods, and alignment methods. The second part presents the alignment method. In this approach the recognition process is divided into two stages. The first determines the transformation in space that is necessary to bring the viewed object into alignment with possible object-models. This stage can proceed on the basis of minimal information, such as the object's dominant orientation, or a small number of corresponding feature points in the object and model. The second stage determines the model that best matches the viewed object. At this stage, the search is over all the possible object-models, but not over their possible views, since the transformation has already been determined uniquely in the alignment stage. The proposed alignment method also uses abstract description, but unlike structural description methods, it uses them pictorially, rather than in symbolic structural descriptions. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1986
Accession Number
ADA184462

Entities

People

  • Shimon Ullman

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Change Detection
  • Character Recognition
  • Computer Vision
  • Computers
  • Content Addressable Memory
  • Image Processing
  • Image Recognition
  • Object Recognition
  • Orientation (Direction)
  • Pattern Recognition
  • Psychology
  • Recognition
  • Three Dimensional
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Business Analytics
  • Computer Vision.

Technology Areas

  • Space
  • Space - Space Objects