Euclidean Position Estimation of Static Features using a Moving Camera with Known Velocities

Abstract

The estimation of 3D Euclidean coordinates of features from 2D images is a problem of significant interest. In this paper we develop a 3D Euclidean position estimation strategy for a static object using a single moving camera whose motion is known. The Euclidean depth estimator which is developed has a very simple mathematical structure and is easy to implement. Numerical simulations and preliminary experimental results using a mobile robot in an indoor environment are presented to illustrate the performance of the algorithm. An extension of this estimation technique for a paracatadioptric system is also presented.

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Document Details

Document Type
Technical Report
Publication Date
Mar 09, 2007
Accession Number
ADA465582

Entities

People

  • Darren Dawson
  • David Braganza
  • Tim Hughes

Organizations

  • Clemson University

Tags

Communities of Interest

  • Air Platforms
  • Autonomy

DTIC Thesaurus Topics

  • Abstracts
  • Aircrafts
  • Algorithms
  • Cameras
  • Computer Programs
  • Engineering
  • Estimators
  • Filters
  • Kalman Filters
  • Kinematics
  • Low Pass Filters
  • Robots
  • Simulations
  • Universities
  • Unmanned Aerial Vehicles
  • Video Cameras
  • Video Surveillance

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Vision.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Autonomy