Parallel Tracking and Mapping for Small AR Workspaces

  • Authors:

  • Georg Klein;David Murray

  • Affiliations:

  • Active Vision Laboratory, Department of Engineering Science, University of Oxford. e-mail: gk@robots.ox.ac.uk;Active Vision Laboratory, Department of Engineering Science, University of Oxford. e-mail: dwm@robots.ox.ac.uk

  • Venue:
  • ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
  • Year:
  • 2007

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Abstract

This paper presents a method of estimating camera pose in an unknown scene. While this has previously been attempted by adapting SLAM algorithms developed for robotic exploration, we propose a system specifically designed to track a hand-held camera in a small AR workspace. We propose to split tracking and mapping into two separate tasks, processed in parallel threads on a dual-core computer: one thread deals with the task of robustly tracking erratic hand-held motion, while the other produces a 3D map of point features from previously observed video frames. This allows the use of computationally expensive batch optimisation techniques not usually associated with real-time operation: The result is a system that produces detailed maps with thousands of landmarks which can be tracked at frame-rate, with an accuracy and robustness rivalling that of state-of-the-art model-based systems.