Motion and Calibration

Computer Analysis of Images and Patterns

Volume 1296 of the series Lecture Notes in Computer Science pp 199-206

Date:

Automated camera calibration and 3D egomotion estimation for augmented reality applications

  • Dieter KollerAffiliated withFraunhofer Project Group for AR at ZGDVEE Dept., California Inst. of TechnologyAutodesk, Inc.
  • , Gudrun KlinkerAffiliated withFraunhofer Project Group for AR at ZGDV
  • , Eric RoseAffiliated withFraunhofer Project Group for AR at ZGDV
  • , David BreenAffiliated withComputer Graphics Lab., California Inst. of Technology
  • , Ross WhitakerAffiliated withEE Dept.
  • , Mihran TuceryanAffiliated withDept of Comp & Info Science, IUPUI

* Final gross prices may vary according to local VAT.

Get Access

Abstract

This paper addresses the problem of accurately tracking the 3D motion of a monocular camera in a known 3D environment and dynamically estimating the 3D camera location. For that purpose we propose a fully automated landmark-based camera calibration method and initialize a motion estimator, which employes extended Kalman filter techniques to track landmarks and to estimate the camera location at any given time. The implementation of our approach has been proven to be efficient and robust and our system successfully tracks in real-time at approximately 10 Hz. We show tracking results of various augmented reality scenarios.