Performance Complexity TradeOffs in H'264 Motion Search

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Performance Complexity Trade-Offs in H.264
Motion Search

• Pooja Agarwal (pagarwal_at_nvidia.com)
• Apoorv Gupta (agupta_at_nvidia.com)
• Paul Kim (pakim_at_nvidia.com)

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Overview

• Outline
• Background on Motion Search
• Motion Estimation in Reference Code
• Our approaches to reduce Motion Search Complexity
• Results
• Conclusion
• Definitions
• Performance Video quality (PSNR)
• Complexity Time taken for Motion Estimation

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Motion Estimation A computation intensive process

• Finding the closest block in the previously
  coded frame (reference frame)
• Closest neighbor is generally the one which has
  the least mean square error (MSE) or sum of
  absolute differences (SAD).
• Motion vector (MV) Displacement
• Full Search in R range gt (2R1)2 computations
  per block

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Motion Estimation Complexity in H.264/AVC

• Multiple reference frames
• Supports a range of different block sizes gt more
  computation per macroblock
• Half-pel and quarter-pel accuracy
• Generalized B-frame and weighted prediction

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Motion Vector Prediction

• What is it?
• Usually there is a high correlation among the
  MVs of the adjacent blocks. Use this to predict
  the motion vector, and calculate the difference
  (MVD).
• Why do it?
• Motion vector encoding can contribute to a
  significant amount of bits per picture,
  especially at low bit rates.
• So transfer only the MVD.

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MV Prediction in H.264 Reference Code

• E current block, and A,B,C are its neighbors
• Predicted-MVE median (MVA, MVB, MVC)
• If one or more block are not available, modify
  the choice accordingly

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Motion Search in H.264 reference Code

• For each macroblock do
• Do ME for all blocks of size 16x16, 16x8, and
  8x16
• Do ME for all blocks of size 8x8 for 8x8 DCT
• Do ME for blocksize 8x8, 4x8, 8x4, and 4x4 for
  4x4 DCT
• Choose the best pel motion vector
• Do sub pixel ME
• Choose the best sub-pel MV

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How to reduce Motion Search space?

• Adaptive reduction in motion search space
• Use a more accurate prediction for MV
• Bias the search to the region around this
  predicted MV and the center of the search space
• C Center of the search range
• MVb New predicted motion vector
• r search range

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Approaches to Motion Vector Prediction

• SAD based motion vector prediction
• Parent based motion vector prediction

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SAD based Motion Vector Predictor

• Predict the motion vector from the neighbor which
  is closest to the current block
• closeness is measured in terms of SAD
• Predicted MV MVAi such that
• SADi min(SAD1, SAD2,
• SAD3, SAD4)
• where SADi SAD(Current, Ai)

• Measured motion vector statistics
• sequence table, 50 frames

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Parent based Motion Vector Predictor

• H.264 reference encoder computes the best motion
  vector starting from biggest block
• We can use the motion vector of parent as the
  predicted MV of the child
• For example, say B is a 16x16 macroblock and A be
  one of its 16x8 partition, then
• Predicted-MV (A) MV(B)

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Results

• Qcif, 100 Frames, 30 Hz

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Results

• Zoomed in version of the previous plot

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Results
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Results

• Qcif, 100 Frames, 30 Hz

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Results
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Conclusion

• Using our predicted motion vectors we were able
  to reduce the search space significantly
• This led to 40 to 50 reduction in the Motion
  Estimation time across five test sequences
  (foreman, table, mobile, tempete,
  mother-daughter)
• The maximum degradation in video quality was
  around 0.2 dB observed in table

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Acknowledgement

• Eric Setton for his valuable guidance throughout
  the project
• Prof. Girod and David Rebollo-Monedero for their
  help

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