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Royalty Cost Based Optimization for Video Compression

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Title: Royalty Cost Based Optimization for Video Compression


1
Royalty Cost Based Optimization for Video
Compression
  • Emrah Akyol, Onur G. Guleryuz, and M. Reha
    Civanlar
  • DoCoMo USA Labs,
  • Palo Alto, CA
  • USA

2
Outline
  • Setup and motivation
  • Problem definition
  • Our solution with some interesting simulation
    results.
  • Conclusion

3
Setup-1 Diverse set of terminals in media
delivery
Required quality/ effective bandwidth
Example terminals decoding the media
content licensing cost 1
Encoding 1
Cell phones
content licensing cost 2
PDAs
Encoding 2
Media



content licensing cost K
HDTVs
Encoding K
Increasing media quality/effective bandwidth
4
Setup-2 Diverse set of tools
Compression tools, error correction tools,
transport tools,
Media data
Tool 1
Tool 3
Tools have different royalty/licensing costs.
Tool 2
Tool 4

Tool T
Decoded Media
(Media Consumer)
5
Thought Experiment
  • Many media delivery technologies available.
  • One can transport media through a variety of
    networks, using a vast range of tools that
    correspond to vast ranges in efficiency in end to
    end delivery.
  • Rather than restricting to rigid toolsets,
    standard profiles, etc., can one be flexible and
    allow all tools to contribute?

Why?
  • Standardization process mostly allows a coarse
    set of options. It mostly caters to the average
    good. Many good tools and technologies get cut
    out because they are not general enough.
    Selection almost always involves compromises.
  • Standardization royalties may force simple tools
    and sophisticated tools equal share of the
    revenue. Impetus for alternative avenues for tool
    deployment.
  • There is movement in this direction (software
    decoders, MPEG RVC, ).
  • MPEG RVC (reconfigurable video coding)
  • put many video compression tools (potentially
    overlapping functionality) in one big library,
  • language syntax to specify which tools are
    needed in decoding a given video stream.

6
Media delivery cost surface
Media Quality
Royalty Cost
Effective Bandwidth
(content licensing tool licensing)
  • Royalty cost of delivering media at a particular
    quality and bandwidth.
  • Example surface defined by achievable quality,
    bandwidth, royalty cost triplets.
  • All triplets below the surface are achievable.

7
Cuts from the surface
Media Quality
h.264/AVC
Royalty Cost
Q
MPEG-1
Effective Bandwidth
8
Complicated Royalty Costs
  • My content costs 5 for cell phone terminals,
    15 for HDTV terminals.
  • My compression tool is free of charge.
  • My compression tool costs 0.001 per use.
  • My tool costs 0.10 per movie, 0.15 for sports,
    ....
  • My tool costs 0.10 except when combined with
    all free tools, in which case it too becomes
    free.
  • My tool is free for not-for-profit use.

9
System Level Media Server
I will mostly talk about compression related tools
10
System Level Media Delivery
Media Server
Registry
User
Certificate can be used to verify
with information from the user site (for each
media segment or periodically) to ensure the
legitimacy of the media.
11
Rate - Distortion - Royalty Cost Optimization
Setup
  • No reason to pay for the latest/greatest tools
  • if plenty of bandwidth
  • if simple/easy content
  • if cheaper tools are available

Problem Definition For each of the M segments,
find the set of tools to use such that distortion
is minimized under total rate and total royalty
cost constraints, i.e.,
s.t.
,

This is a simplification. Optimization can get
elaborate.
12
Optimization Example Using Compression Tools
  • Case 1 Flat Rate, similar to todays
    licensing.
  • Case 2 Fair Rate, each tool gets paid based
    on its contribution

Table I Assigned cost of using each tool for two
different cases

Table II Rate and distortion changes with
different tools. The utilized tools are subpixel
accurate ME, loop filter, advanced entropy
coding, and multiple reference frames
respectively. The rate reduction is shown as
percentage with respect to the baseline along
with PSNR gain at QP25.
13
Flat Rate
Quality
  • concatenation of 10 clips
  • Significant reduction in royalty costs with
    small loss in efficiency
  • Inefficient tools get cut out (lobbying for
    tools is useless).
  • Adaptive constant
  • Constant toolset Optimized tools for the entire
    duration of the content.
  • Adaptive toolset Optimized tools for each GOP
    (toolset can change every GOP media segment)

14
Fair Rate
Quality
  • Adaptive better than constant.
  • Significant reductions are difficult.

15
Tool Usage
  • Adaptive allows more tools to contribute (tools
    that are good in niche situations get used).

Flat Rate
Fair Rate
16
Conclusion
  • A system that allows practical deployment of
    royalty cost optimized media delivery.
  • Very interesting optimization problem with
    sophisticated royalty costs.
  • Content adaptive.
  • Increases efficiency. Allows non-standard tools
    to contribute.
  • Much reduced royalties when plenty of
    bandwidth/resources.
  • Flat rate significant reductions in royalty
    cost possible.
  • Fair rate significant reductions difficult.
  • Adaptive optimization allows each tool to
    contribute when its niche comes.
  • Can allow other resources relevant to media
    delivery into optimization (power consumption,
    memory usage, etc.)
  • Going forward
  • Optimization issues.
  • More tools.
  • Dependencies among tools.
  • Addition of communication/networking related
    tools.
  • Fair rate
  • Allow segment based licensing

17
Going forward How should tools be priced?
  • Combines game theory and economic concepts with
    rate-distortion
  • How much are customers willing to pay to get
    quality Q at bandwidth B? (Utilization curves).
  • Optimal costs based on utilization curves and
    game theory.
  • What does todays licensing look like?
  • Games

D,R not achievable
free region
Distortion
Free
T1 cost1(R)
T2 cost2(R)
T1 T2 cost3(R)
R
Rate
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