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Proceedings Paper

Rule-based segmentation for intensity-adaptive fiducial detection
Author(s): Jong-Weon Lee; Ulrich Neumann
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Paper Abstract

This paper describes a new fiducial detection method for use under varying lighting conditions without manual control of any parameters. We developed the algorithm especially for vision-based Augmented Reality (AR) systems. The major problem in AR is the registration between the virtual world and the real world. The user's pose in both worlds should be exactly the same. Vision-based AR is an attractive approach to the registration problem, however the fiducial detection methods used in many systems operate only under restricted lighting conditions. We developed a rule-based algorithm to segment regions of an image to detect known fiducials under varying lighting conditions. The algorithm is based on simple spatial and intensity relations among fiducials and their backgrounds. Rules and membership functions are defined from those relations. Rules are applied to find transition regions, and membership functions locate an edge position within a transition region. Edges are clustered to segment regions in an image. A vision-based AR system using our method operates under varying lighting conditions, including uneven lighting. This detection method extends the operating conditions of vision-based AR systems.

Paper Details

Date Published: 17 May 1999
PDF: 9 pages
Proc. SPIE 3642, High-Speed Imaging and Sequence Analysis, (17 May 1999); doi: 10.1117/12.348425
Show Author Affiliations
Jong-Weon Lee, Univ. of Southern California (United States)
Ulrich Neumann, Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 3642:
High-Speed Imaging and Sequence Analysis
Alan M. Frank; Alan M. Frank; James S. Walton, Editor(s)

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