International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Landmark Initialization for Unscented Kalman Filter Sensor Fusion in Monocular Camera Localization

  • Hartmann, Gabriel (Server and Tools Division at Microsoft, Microsoft Redmond Campus) ;
  • Huang, Fay (Computer Science and Information Engineering, National Ilan University) ;
  • Klette, Reinhard (Computer Science Department, The University of Auckland)
  • Received : 2013.02.25
  • Accepted : 2013.03.15
  • Published : 2013.03.25
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Abstract

The determination of the pose of the imaging camera is a fundamental problem in computer vision. In the monocular case, difficulties in determining the scene scale and the limitation to bearing-only measurements increase the difficulty in estimating camera pose accurately. Many mobile phones now contain inertial measurement devices, which may lend some aid to the task of determining camera pose. In this study, by means of simulation and real-world experimentation, we explore an approach to monocular camera localization that incorporates both observations of the environment and measurements from accelerometers and gyroscopes. The unscented Kalman filter was implemented for this task. Our main contribution is a novel approach to landmark initialization in a Kalman filter; we characterize the tolerance to noise that this approach allows.

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References

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