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Authors: Ferdous Ahmed Sohel Dr. Gour Chandra Karmakar Prof. Laurence Sean Dooley

Presenter: A/Prof. Manzur Murshed Gippsland School of Information Technology, Monash University AUSTRALIA. Dynamic Sliding Window Width Selection Strategies for Rate-Distortion Optimal Vertex-Based Shape Coding Algorithms. Authors: Ferdous Ahmed Sohel Dr. Gour Chandra Karmakar

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Authors: Ferdous Ahmed Sohel Dr. Gour Chandra Karmakar Prof. Laurence Sean Dooley

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  1. Presenter: A/Prof. Manzur MurshedGippsland School of Information Technology, Monash University AUSTRALIA. Dynamic Sliding Window Width Selection Strategies for Rate-Distortion Optimal Vertex-Based Shape Coding Algorithms Authors: Ferdous Ahmed Sohel Dr. Gour Chandra Karmakar Prof. Laurence Sean Dooley Gippsland School of Information Technology, Monash University.

  2. Presentation Outline • Introduction to the vertex-based shape coding algorithms • Influence and importance of the sliding window and its width • Sliding window width determining techniques • Experimental results • Conclusion.

  3. Introduction: Shape Coding Object Segmentation Grey Scale Foreground Object Natural Image/ Video Frame Grey to binary Object Shape/ Binary alpha-plane of the object

  4. Introduction: Shape Coding Bit-map based coding: e.g., Context-based Arithmetic Encoder (CAE) Group 4 (G4) Modified Modified Read (MMR) Contour based coding: e.g., Polygon-based coding Polynomial-based coding Base-line based coding

  5. Rate information Encoder … 01011 … 0010… Distortion information Contour-based Shape Coding Polynomial-based coding

  6. Polynomial-based coding • Two basic frameworks • Polygon based(requires 2 control points for each edge segment) • B-spline based (quadratic, requires 3 control points for each curve segment) Considers weighted directed acyclic graph (DAG) based dynamic programming Single source (starting vertex); Single destination (last vertex)

  7. Polynomial-based coding DAG Formation : For 5 contour-points Quadratic B-spline Polygon: (ai, aj) if i<j w()’s are determined based on the distortion property and required bit-rate

  8. w(ai,aj)=D(ai,aj)+ R(ai,aj) Differentially encode vertex aj given vertex ai is already encoded. =0, if the admissible distortion is maintained =INFINITY, otherwise Polynomial-based coding Polygon based There are similar methods for the B-spline based framework.

  9. Shape corners: NOT preserved Trivial Solutions Since, all (ai,aj) if i<j are in the DAG Potential source of computational cost Problems without a Sliding Window Computationally inefficient

  10. Influence of Sliding Window Shape corners: Preserved No trivial solution Avoids unnecessary computations

  11. Effect of the SW Width on the bit-rate and CPU time requirements Sliding window enforces the encoder to select the next control point within the width A smaller SW width means a higher bit-rate requirement Sliding window limits the search space for the next control point within the width A smaller SW width means a computationally faster encoding

  12. SW-width has a direct and large impact on the bit-rate irrespective of the admissible distortion Diminishing effect with large SW SW-width has a little impact on the admissible distortion for a given bit-rate Effect of the SW Width on the bit-rate and admissible distortion

  13. SW-width determination for a given bit-rate A number of important factors: Admissible bit-rate (Rmax): Larger bit-rate can effort a smaller width. Length of the shape contour (NB): Longer contour enforces a wider SW Different codebook: To encode the same vertex different bit-rate may be required. c is the average number of bits required to encode a control point. A number of mechanisms has been presented to determine c for different codebooks and probability models in the paper.

  14. SW-width determination for a given admissible distortion Little regularity with the admissible distortion

  15. Preserves the sharp corners of a shapes Computationally efficient Fits very well in either rate or distortion constrained encoder. Advantages: Shape adaptive SW-width Utilises the shape’s curvature information A high curvature point has a narrower SW A low curvature point has a wider SW This is obtained by mapping between the SW-width and the curvature. The bounds are obtained from the code book and the shape.

  16. Results: Effect of SW-width on CPU time and Bit-rate Miss America: Neck Dmax =1 pel

  17. Results: SW-width estimation for admissible bit-rate Estimated SW-width with constrained bit-rate obtained distortion and utilisation of bit-rate

  18. Results: Adaptive SW Shape curvatures are better preserved. Gradual parts support wider SW. So efficiently utilises the bit rate

  19. Results: Adaptive SW (Time and bit-rate comparisons)

  20. Additional Results: Adaptive SW (Kids)

  21. Conclusion • Formalised the use of the Sliding window (SW) • The SW-width makes a trade-off between the bit-rate and computational time requirements • Determines the most appropriate SW-width for a given admissible bit-rate for a range of codebooks and probability models • Dynamically determines the SW-width based on the shape curvature information in either of bit-rate or distortion constraint coder.

  22. Authors’ E-mails Ferdous.Sohel@infotech.monash.edu.au Gour.Karmakar@infotech.monash.edu.au Laurence.Dooley@infotech.monash.edu.au

  23. Thank you

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