Level Set Segmentation with Shape Priors - PowerPoint PPT Presentation

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Level Set Segmentation with Shape Priors

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Level Set Segmentation with Shape Priors Jue Wang and Jiun-Hung Chen CSE/EE 577 Spring 2004 Notes on Level Set Steps for implementation Define your own energy ... – PowerPoint PPT presentation

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Title: Level Set Segmentation with Shape Priors


1
Level Set Segmentation with Shape Priors
  • Jue Wang and Jiun-Hung Chen
  • CSE/EE 577 Spring 2004

2
Notes on Level Set
  • Steps for implementation
  • Define your own energy functional
  • Initialize the curve and surface
  • Evolve according to the numerical solution
  • Continue until stopping criteria is reached

3
Notes on Level Set
  • So the key is
  • Defining a good energy function
    according to your application
  • For basic image segmentation, the energy
    functional is usually defined as

4
Notes on Level Set
  • Numerical Implementation
  • Not easy to figure out but theyre in books, for
    example
  • Numerical stability should be also considered
    when you design your own energy function

5
Segmentation with Shape Prior
Reference shape
Level set seg. w/o shape prior
Level set seg. w/ shape prior
Input image
D. Cremers and S. Soatto. A pseudo-distance for
shape priors in level set segmentation. IEEE
Workshop on Variational, Geometric and Leve Set
Methods in Computer Vision, 2003.
6
Segmentation with Shape Prior
  • Basic Idea
  • Shape prior can be represented as another
    implicit function
  • The evolution of current is influenced by
    the distance between and .
  • Problem how to define the distance

7
Segmentation with Shape Prior
  • A Pseudo-distance
  • Shape energy
  • Evolution function

8
Segmentation with Shape Prior
  • Pose parameters
  • Numerical solution help needed for this ?

9
Results
  • An images worth of thousands of words
  • An EXE is worth more

10
Future Work
  • How to incorporate statistical shape models?
  • Have a bunch of reference shapes instead of one
  • X.M. et al. Integrating prior shape models into
    level-set approaches. Pattern Recognition
    Letters, April 2004.
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