1 / 29

Balanced Parallel Scheduling for Video Encoding with Adaptive GOP Structure

Balanced Parallel Scheduling for Video Encoding with Adaptive GOP Structure. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 24, NO. 12, DECEMBER 2013 Hsu- Feng Hsiao, Member, IEEE, and Chen-Tsang Wu. Outline. Introduction Related Work Methods Experimental Results.

liana
Download Presentation

Balanced Parallel Scheduling for Video Encoding with Adaptive GOP Structure

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Balanced Parallel Scheduling for Video Encoding with Adaptive GOP Structure IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 24, NO. 12, DECEMBER 2013 Hsu-Feng Hsiao, Member, IEEE, and Chen-Tsang Wu

  2. Outline • Introduction • Related Work • Methods • Experimental Results

  3. Introduction • Idea 1: • Scene change • Idea 2: • Scheduling

  4. Related Work #1 • Scene change detection • Abrupt scene change • An abrupt scene change indicates that transition from one scene into another only spends a period of one frame. • Gradual scene change • A gradual scene change takes a period of several frames to complete a scene transition.

  5. Related Work #2 • Pixel-based method • Sum of mean absolute difference (SMAD) • Block-based method • A scene change is declared if the ratio of similar blocks between two frames is greater than some threshold.

  6. Related Work #3 • Frame-level parallelism

  7. Method #1 • Sum of absolute temporal difference (SATD) • Where is the pixel value at location (x,y).

  8. Method #2 • Sum of absolute spatial difference (SASD)

  9. Method #3 • Sum of absolute spatial difference (SASD)

  10. Method #4

  11. Method #5 • Abrupt Scene Change Detection Algorithm • If Ratio is greater than the predefined threshold Abrupt Scene Change

  12. Method #6 • Ratio noise • Threshold = 1.4

  13. Method #7

  14. Method #8 • 2nd derivative • Local maxima of the ratios shall be at the positions where the values are negative. • Threshold = -1.0

  15. Method #9 • Gradual Scene Change Detection Algorithm • A gradual scene change takes a period of several frames • Ratio(n,m) is the ratio between frame n and frame m.

  16. Method #10 • Beginning • Threshold = 0.7(0.3~1.0) • Ending • Convergence

  17. Method #11

  18. Method #12

  19. Method #13 I : 120ms B : 290ms P : 360ms

  20. Method #14

  21. Method #15

  22. Method #16

  23. Method #17

  24. Experimental Results #1

  25. Experimental Results #2

  26. Experimental Results #3

  27. Experimental Results #4

  28. Experimental Results #5

  29. Experimental Results #6

More Related