Machine Recognition as Representation and Search

Abstract

Generality, representation, and control have been the central issues in machine recognition. Model-based recognition is the search for consistent matches of the model and image features. We present a comparative framework for the evaluation of different approaches, particularly those of ACRONYM, RAF, and Ikeuchi et al. The strengths and weaknesses of these approaches are discussed and compared and the remedies are suggested. Various tradeoffs made in the implementations are analyzed with respect to the systems' intended task-domains. The requirements for a versatile recognition system are motivated. Several directions for future research are pointed out. Keywords: Computer vision, Model-based recognition, Representation, Object modeling, Search control, Consistent labeling.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1989
Accession Number
ADA223700

Entities

People

  • Feng Zhao

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Artificial Intelligence
  • Computer Vision
  • Coordinate Systems
  • Geometry
  • Identification
  • Image Processing
  • Model Tests
  • Normal Distribution
  • Object Recognition
  • Pattern Recognition
  • Recognition
  • Shape
  • Test And Evaluation
  • Three Dimensional
  • Trees (Data Structures)

Readers

  • Computational Modeling and Simulation
  • Computer Vision.
  • Joint Military Operations and Doctrine.

Technology Areas

  • AI & ML