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Feature detection and tracking in three dimensional image analysis

  • Avner Friedman
Chapter
  • 148 Downloads
Part of the The IMA Volumes in Mathematics and its Applications book series (IMA, volume 67)

Abstract

Advances in sensor and computer technology are resulting in an increased use of three-dimensional images in applications such as medical diagnosis, video understanding, and fluid dynamics. In these applications, each gray level represents certain relevant property associated with the location (i, j, k) in the modeled three-dimensional world. The ability to detect features and/or track them over time is the ultimate goal in the automatic analysis of these images.

Keywords

Principal Curvature Vortex Core Feature Detection Computation Fluid Dynamics Topographic Classification 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    D. Marr and E. Hildreth, Theory of edge detection, Proc. Royal Soc. London, B 207 (1980), 187–217.CrossRefGoogle Scholar
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    W.E. Lorensen and H.E. Cline, Marching cubes: A high resolution 3D surface construction algorithm, ACM Computer Graphics, 21 (1987), 663–169.CrossRefGoogle Scholar
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    S.P. Liou, and A. Singh, High-resolution 3D edge detection for non-uniformly sampled edges,to appear.Google Scholar
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    R.M. Haralick, L.T. Watson and T.J. Laffey, The topographic primal sketch, The International Journal of Robotic Research, 2 (1983), 5072.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag New York, Inc. 1995

Authors and Affiliations

  • Avner Friedman
    • 1
  1. 1.Institute for Mathematics and its ApplicationsUniversity of MinnesotaMinneapolisUSA

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