Selecting Promising Landmarks

Abstract

Many approaches to visual servoing and mobile robot navigation are based on tracking feature points or landmarks on images. But are all features points equally effective as landmarks? Here we develop methods for selecting within an image those landmarks which are both perceptually salient and visually distinctive, and consequently are readily recognized in a second image acquired from a different viewpoint. Empirically, we characterize the performance of the recognition method and then demonstrate that the selection process does in fact choose the landmarks which are more likely to be recognized.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2000
Accession Number
ADA640014

Entities

People

  • David J. Kriegman
  • Markus Knapek
  • Ricardo S. Oropeza

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Air Platforms
  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Automation
  • Autonomous Navigation
  • Computer Science
  • Computer Vision
  • Computers
  • Digital Images
  • Images
  • Information Operations
  • Navigation
  • Recognition
  • Robot Navigation
  • Robotics
  • Robots
  • Rotation
  • Three Dimensional
  • Visual Servoing

Fields of Study

  • Computer science

Readers

  • Computer Vision.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy