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Stochastic Analysis of Scale-Space Smoothing

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Author

Summary, in English

In the high-level operations of computer vision it is taken for granted that image features have been reliably detected. This paper addresses the problem of feature extraction by scale-space methods. This paper is based on two key ideas: to investigate the stochastic properties of scale-space representations, and to investigate the interplay between discrete and continuous images. These investigations are then used to predict the stochastic properties of sub-pixel feature detectors

Publishing year

1996

Language

English

Pages

305-309

Publication/Series

13th International Conference on Pattern Recognition

Volume

2

Document type

Conference paper

Publisher

IEEE - Institute of Electrical and Electronics Engineers Inc.

Topic

  • Mathematics

Keywords

  • computer vision
  • correlation methods
  • feature extraction
  • interpolation
  • smoothing methods
  • stochastic processes

Conference name

13th International Conference on Pattern Recognition, (ICPR 1996)

Conference date

1996-08-25 - 1996-08-29

Conference place

Vienna, Austria

Status

Published

ISBN/ISSN/Other

  • ISBN: 0 8186 7282 X