rate-distortion optimal skeleton-based shape coding haohong wang, aggelos k. katsaggelos, and...
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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
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Outline
Introduction Skeleton-Based Shape Representation Lossy Coding of Shape Data Experimental Results Conclusions
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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
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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
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Skeleton-Based Shape Representation
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Skeleton-Based Shape Representation 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
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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.
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Coding of Shape Data
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Polygonal approximation
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Lossy Coding of Shape Data
To solve the problem :
max1010 ),...(:),,...(min RPPRtosubjectPPD NN
max1010 ),...(:),,...(min DPPDtosubjectPPR NN
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Lossy Coding of Shape Data
Distortion function– The sum of the absolute value of the errors
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Lossy Coding of Shape Data
Lossless skeleton and lossy distance data coding
sdN RRRtosubjectppD max10 :),,...(min
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Lossy Coding of Shape Data
Lossy coding of both skeleton and distance data
To minimize
max1010 :)],,...(),...([min RRRtosubjectqqDppD dsMdNs
)( dsds RRDD
pixelsInteriorofNumber
errorinpixelsofNumberDMPEG 4
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Lossy Coding of Shape Data
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Experimental Results
polygonspline
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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.
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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.