1. Rate-Distortion Optimal Skeleton-Based Shape Coding Haohong Wang, Aggelos K. Katsaggelos, and Thrasyvoulos N. Pappas Image Processing, 2001. Proceedings. 2001 International Conference on, Oct 2001

2. Outline Introduction Skeleton-Based Shape Representation Lossy Coding of Shape Data Experimental Results Conclusions

3. Introduction Shape coding –Block-based –Contour-based Chain Code Baseline Vertex-based (polygon/B-spline approximation) The binary shape of an object is defined by

4. Skeleton-Based Shape Representation The basic idea : –To represent an object by one or more 2D curves (skeletons with associated distance data) Skeletons –The center of the object in the horizontal direction Distance data –The associated distance from the boundary

5. Skeleton-Based Shape Representation

6. More flexibility –Different transform and compression methods for each data set, according to their characteristics. The skeletons can be used for the estimation of the object motion in the Inter-mode

7. Coding of Shape Data Different characteristics –The object has near axial symmetry => the skeleton will be smooth –The two boundaries are nearly parallel => the distance function will be smooth The experimental results verify that the decoupling provides a compression advantage.

8. Coding of Shape Data

9. Polygonal approximation

10. Lossy Coding of Shape Data To solve the problem :

11. Lossy Coding of Shape Data Distortion function –The sum of the absolute value of the errors

12. Lossy Coding of Shape Data Lossless skeleton and lossy distance data coding

13. Lossy Coding of Shape Data Lossy coding of both skeleton and distance data To minimize

14. Lossy Coding of Shape Data

15. Experimental Results polygon spline

16. Conclusions By decoupling the shape object data into the skeleton and distance data, the scheme reduces their correlation. The approach together with polygonal approximation of the skeleton and the distance data results in a significant improvement in rate-distortion efficiency.

17. Conclusions Which is the suitable algorithm for compressing the skeleton and the distance data? The skeleton and distance data can be predicted from the previous frame.