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Aditya Mavlankar, Pierpaolo Baccichet, D avid Varodayan and Bernd Girod

Optimal Slice Size for Streaming Regions of High-Resolution Video with Virtual Pan/Tilt/Zoom Functionality. Aditya Mavlankar, Pierpaolo Baccichet, D avid Varodayan and Bernd Girod Information Systems Laboratory Stanford University. TexPoint fonts used in EMF.

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Aditya Mavlankar, Pierpaolo Baccichet, D avid Varodayan and Bernd Girod

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  1. Optimal Slice Size for Streaming Regions of High-Resolution Video withVirtual Pan/Tilt/Zoom Functionality Aditya Mavlankar, Pierpaolo Baccichet, David Varodayan and Bernd Girod Information Systems Laboratory Stanford University TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: AAAAAA

  2. Outline • High-resolution video streaming with IROI • Proposed coding scheme for IROI video streaming • Analysis of optimal slice size selection • Experimental results

  3. High-Resolution Video Streaming with IROI • Related work • Interactive image browsing with JPEG-2000 [Taubman et al. 2003] • Interactive streaming of lightfields [Ramanathan et al. 2004] • Interactive streaming of panoramic videos [Heymann et al. 2005] • ... • Sources of high-resolution videos • High-resolution digital imaging sensors (CMOS technology) • High-resolution videos stitched from multiple cameras • Application scenarios • Surveillance • Instructional videos • Snow cams in ski resorts • Interactive TV with virtual pan/tilt/zoom • ...

  4. Demo

  5. H.264/AVC Based Coding Scheme ROI Resolution layer N - ↑ ROI Resolution layer 1 - ↑ P slices Overview video Hierarchical B pictures

  6. Pixel Overhead ROI Tradeoff due to Slice Size Small slice size • Entire scene takes more bits to encode • Slice headers • Lack of context continuation across slices for context adaptive coding • Cannot exploit inter-pixel correlation across slices • Less pixel overhead: Can adapt to ROI due to fine granularity of slice grid

  7. 2.5 0.5 2 0.4 Number of pixels transmitted per rendered pixel Bit per pixel for coding given layer 1.5 0.3 1 0.2 32x32 64x64 128x128 160x160 Slice size in pixels [ ] Tradeoff Observed for Pedestrian Area, layer 2

  8. 0.6 0.55 0.5 Bits transmitted per rendered pixel 0.45 0.4 32x32 64x64 128x128 160x160 Slice size in pixels [ ] Tradeoff Observed for Pedestrian Area, layer 2

  9. 2.5 0.4 2 0.3 Number of pixels transmitted per rendered pixel Bit per pixel for coding given layer 1.5 0.2 1 0.1 32x32 64x64 128x128 160x160 Slice size in pixels [ ] Tradeoff Observed for Pedestrian Area, layer 3

  10. 0.4 0.38 0.36 0.34 Bits transmitted per rendered pixel 0.32 0.3 0.28 32x32 64x64 128x128 160x160 Slice size in pixels [ ] Tradeoff Observed for Pedestrian Area, layer 3

  11. Pixel Overhead Analysis in 1-D Imagine an infinitely long line of pixels. In this example, segment index SOI SOI SOI SOI # pixels transmitted (random variable)

  12. Pixel Overhead Analysis in 2-D ROI Expected number of pixels transmitted

  13. Optimization Criterion and Constraints • Practical constraints narrow down the search: • slice dimensions have to be multiples of macroblock width • many values can be ruled out since they are likely to be suboptimal • constraints due to display dimensions, e.g., restrictions on translation of ROI Number of pixels transmitted per rendered pixel Bit per pixel for coding given layer

  14. 2.5 0.5 2 0.4 Number of pixels transmitted per rendered pixel Bit per pixel for coding given layer 1.5 0.3 1 0.2 32x32 64x64 128x128 160x160 Slice size in pixels [ ] Model Vs Experimental Results (Pedestrian Area, layer 2) Model Experiments

  15. 0.6 0.55 0.5 Bits transmitted per rendered pixel 0.45 0.4 32x32 64x64 128x128 160x160 Slice size in pixels [ ] Model Vs Experimental Results (Pedestrian Area, layer 2) Model Experiments

  16. 2.5 0.4 2 0.3 Number of pixels transmitted per rendered pixel Bit per pixel for coding given layer 1.5 0.2 1 0.1 32x32 64x64 128x128 160x160 Slice size in pixels [ ] Model Vs Experimental Results (Pedestrian Area, layer 3) Model Experiments

  17. 0.4 0.38 0.36 0.34 Bits transmitted per rendered pixel 0.32 0.3 0.28 32x32 64x64 128x128 160x160 Slice size in pixels [ ] Model Vs Experimental Results (Pedestrian Area, layer 3) Model Experiments

  18. Summary • Coding scheme provides random access to • arbitrary resolutions • arbitrary spatial regions within every resolution • Slice size is optimized given • the video signal • the QP • the ROI display area dimensions • Other coding parameters could be further optimized, for example, joint selection of the QP for the base layer and the enhancement layers

  19. The End

  20. Backup Slides Follow Hereafter

  21. Overview display area ROI display area Parts of the Client’s Display

  22. ROI Original video is available in resolutions by for , i.e., highest resolution and Region-of-Interest Trajectory ROI ROI

  23. Pixel Overhead Analysis in 1-D Imagine an infinitely long line of pixels. In this example, segment index SOI SOI SOI SOI Pixel Overhead • Theorem: Given that , • increases monotonically with • is independent of

  24. Pixel Overhead Analysis in 2-D ROI Expected value of pixel overhead in 2-D Expected number of pixels to be transmitted

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