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Towards View-Aware Adaptive Streaming of Holographic Content

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Holography is able to reconstruct a three dimensional structure of an object by recording full wave fields of light emitted from the object. This requires a huge amount of data to be encoded, stored, transmitted, and decoded for holographic content, making it a practical usage challenging, specifically for bandwidth-constrained networks and memory-limited devices. In the delivery of holographic content via the internet, bandwidth wastage should be avoided to tackle high bandwidth demands of holography streaming. For real-time applications, encoding time-complexity is also a major problem. In this paper, the concept of Dynamic Adaptive Streaming over HTTP (DASH) is extended to holography image streaming and view-aware adaptation techniques are studied. As each area of a hologram contains information of a specific view and instead of encoding and decoding the entire hologram, just the part required to render the selected view is encoded and transmitted via the network based on the users’ interactivity. Four different strategies, namely, (i) monolithic, (ii) single view, (iii) adaptive view, and (iv) non-real time streaming are explained and compared in terms of (a) bandwidth requirements, (b) encoding time-complexity, and (c) bitrate overhead. Experimental results show that the view-aware methods reduce the required bandwidth for holography streaming at the cost of a bitrate increase.

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Towards View-Aware Adaptive Streaming of Holographic Content

  1. 1. Towards View-Aware Adaptive Streaming of Holographic Content Hadi Amipour1, Christian Timmerer1,2, and Mohammad Ghanbari1,3 1Alpen-Adria-Universität Klagenfurt, Klagenfurt, Austria 2Bitmovin, Klagenfurt, Austria 3School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK This research has been supported in part by the Christian Doppler Laboratory ATHENA: https://athena.itec.aau.at/
  2. 2. Challenges for digital holographic video display systems 2 01 Displays Very premature and heterogeneouse in design No established standard how to supply holographic data to the display 02 Recording Recording at high resolution is difficult Require expertise to build and operate 03 CGH More calculation-intensive than classical image rendering 04 Coding New transform is needed for digital holograms 05 QoE Accurate model is required for modelling perceptual visual quality
  3. 3. Workflow for end-to-end hologram delivery 3Signal processing challenges for digital holographic video display systems
  4. 4. 4 Dataset The dataset consists of diffuse holograms generated from 3D point clouds  Interfere-II  Resolution: 8192 x 8192  Pixel pitch: 1 um  Wavelength: 633 nm  Field of view: 370°  Full parallax
  5. 5. 5 Compression  Each hologram is stored as a matrix that contains complex numbers.  In order to encode each hologram in the hologram plane, each raw hologram is divided into two parts, real and imaginary.  Both real and imaginary parts are encoded using an ordinary image/video encoder.
  6. 6. 6 Viewports  Each hologram contains information of all views of an object  To render each requested view, the corresponding area of that view in the hologram is extracted
  7. 7. Adaptive holography streaming 7 01 Monolithic streaming 02 Single view streaming 03 Adaptive view streaming 04 Non-real time streaming
  8. 8. 8 Monilithic streaming  The entire hologram is sent. The delivery of out of viewport areas of a holographic content leads to bandwidth wastage  Increased encoding/decoding time-complexity  Best user interactivity streaming HTTPSeg1Seg1 Highest bitrateLowest bitrate HTTP Server Client Select viewDecoder
  9. 9. 9 Single view streaming  One view is requested and the corresponding segment is transmitted  Highest possible bandwidth reduction  Reduces encoding/decoding time-complexity  It is impractical in user interactive hologram
  10. 10. 10 Single view streaming  One view is requested and the corresponding segment is transmitted  Highest possible bandwidth reduction  Reduces encoding/decoding time-complexity  It is impractical in user interactive hologram HTTPSeg_1Seg_1 Highest bitrateLowest bitrate HTTP Server Client Select view Decoder Seg_2 Seg_N Seg_2 Seg_N
  11. 11. 11 Adaptive view streaming  Each partition of holograms is extended to a larger partition  Increases the user experience HTTPSeg_1Seg_1 Highest bitrateLowest bitrate HTTP Server Client Select view Decoder Seg_2 Seg_N Seg_2 Seg_N d d = 256  512x512 views
  12. 12. 12 Adaptive view streaming  Each partition of holograms is extended to a larger partition  Increases the user experience d d = 256  512x512 views
  13. 13. 13 Non-real time streaming  For each hologram 8192x8192 single views should be stored 2048 1024
  14. 14. 14 Bandwidth  Bandwidth requirements for various streaming strategies
  15. 15. 15 Bandwidth  Bandwidth requirements for various streaming strategies
  16. 16. 16 Bandwidth  Bandwidth requirements for various streaming strategies
  17. 17. 17 Time Complexity  Encoding time-complexity for various streaming strategies  Results divided to max value
  18. 18. Conclusion 18 01 Monolithic streaming  The entire hologram is encoded and transmitted  Requires the highest bandwidth and encoding/decoding time complexity  All views are available in the client side 02 Single view streaming  Only one view is transmitted  Requires the lowest bandwidth and encoding/decoding time complexity  Impractical in user interactive display systems 03 Adaptive view streaming  In addition to the requested viewport, its neighboring views are transmitted  Efficient in terms of bandwidth consumption  A trade-off is established between user interactivity and bandwidth consumption 04 Non-real time streaming  The overall bitrate increases compared to the monolithic streaming  The storage space is decreased compared to the single/adaptive view streaming
  19. 19. 19 www.athena.itec.aau.at Any Questions? /HadiAmirpour

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