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

2. 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. 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. 4 Notes on Level Set Numerical Implementation  Not easy to figure out but they’re in books, for example  Numerical stability should be also considered when you design your own energy function

5. 5 Segmentation with Shape Prior Reference shape Input image Level set seg. w/o shape prior Level set seg. w/ shape prior 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. 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. 7 Segmentation with Shape Prior A Pseudo-distance Shape energy: Evolution function:

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

9. 9 Results An image’s worth of thousands of words An EXE is worth moreEXE

10. 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.