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Families of tuned scale-space kernels

  • L. M. J. Florack
  • B. M. ter Haar Romeny
  • J. J. Koenderink
  • M. A. Viergever
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 588)

Abstract

We propose a formalism for deriving parametrised ensembles of local neighbourhood operators on the basis of a complete family of scale-space kernels, which are apt for the measurement of a specific physical observable. The parameters are introduced in order to associate a continuum of a priori equivalent kernels with each scale-space kernel, each of which is tuned to a particular parameter value.

Ensemble averages, or other functional operations in parameter space, may provide robust information about the physical observable of interest. The approach gives a possible handle on incorporating multi-valuedness (transparancy) and visual coherence into a single model.

We consider the case of velocity tuning to illustrate the method. The emphasis, however, is on the formalism, which is more generally applicable.

Keywords

Stimulus Velocity Complete Family Functional Operation Point Stimulus Stereo Disparity 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • L. M. J. Florack
    • 1
  • B. M. ter Haar Romeny
    • 1
  • J. J. Koenderink
    • 2
  • M. A. Viergever
    • 1
  1. 1.3D Computer Vision Research GroupUniversity HospitalCX UtrechtThe Netherlands
  2. 2.Dept. of Medical and Physiological PhysicsUniversity of UtrechtCC UtrechtThe Netherlands

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