Accurate Camera Calibration for Off-line, Video-Based Augmented Reality

  • Authors:
  • Simon Gibson;Jon Cook;Toby Howard;Roger Hubbold;Dan Oram

  • Affiliations:
  • -;-;-;-;-

  • Venue:
  • ISMAR '02 Proceedings of the 1st International Symposium on Mixed and Augmented Reality
  • Year:
  • 2002

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Abstract

Camera tracking is a fundamental requirement for video-based Augmented Reality applications. The ability to accurately calculate the intrinsic and extrinsic camera parameters for each frame of a video sequence is essential if synthetic objects are to be integrated into the image data in a believable way. In this paper, we present an accurate and reliable approach to camera calibration for off-line video-based Augmented Reality applications.We first describe an improved feature tracking algorithm, based on the widely used Kanade-Lucas-Tomasi tracker. Estimates of inter-frame camera motion are used to guide tracking, greatly reducing the number of incorrectly tracked features. We then present a robust hierarchical scheme that merges sub-sequences together to form a complete projectivereconstruction. Finally, we describe how RANSAC-based random sampling can be applied to the problem of self-calibration, allowing for more reliable upgrades to metric geometry. Results of applying our calibration algorithms are given for both synthetic and real data.