Aspects of Invariants for Object Recognition

Abstract

This report is the Final Report for this contract. It details the work done since our last progress report and provides a summary of all the achievements and results that we have obtained. In particular, it details our success in applying newly developed techniques from geometric invariant theory and shape theory, including discrimination metrics, to problems in target recognition. One of the most significant successes was the creation of a global theory of object/image equations for point features in the generalized weak perspective case. These equations offer a necessary and sufficient, pose independent, robust test for geometric consistency between an object and a purported image of that object. The work also included the development of optimal discrimination metrics and the proof of a metric duality result that shows one can work in either image space or object space to create a natural notion of distance between an object and an image. In addition, similar results were obtained in the radar case (orthographic projection) where the shape spaces, object/image equations, and metrics were worked out explicitly for small numbers of feature points.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2004
Accession Number
ADA426885

Entities

People

  • Peter F. Stiller

Organizations

  • Texas Engineering Experiment Station

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algebraic Geometry
  • Computer Science
  • Computer Vision
  • Detectors
  • Differential Geometry
  • Discrimination
  • Engineering
  • Equations
  • Geometry
  • Mathematics
  • Military Research
  • Object Recognition
  • Recognition
  • Target Recognition
  • Topology

Fields of Study

  • Computer science

Readers

  • Calculus or Mathematical Analysis
  • Computer Vision.
  • Theoretical Analysis.

Technology Areas

  • Space
  • Space - Space Objects