On Combining Temporal Scaling and Quality Scaling for Streaming MPEG

1
On Combining Temporal Scaling and Quality
Scaling for Streaming MPEG
Huahui Wu, Mark Claypool, Robert Kinicki
Computer Science, Worcester Polytechnic
Institute
2
Introduction

• Streaming video
• Bitrate gt Network capacity
• Media Scaling
• Temporal Scaling (TS) or Quality Scaling (QS)
• Packet loss
• Forward Error Correction (FEC)
• Operations Research algorithm
• To satisfy capacity constraint
• To maximize perceived quality
• Previous research
• Temporal Scaling TOMCCAP 05
• Quality Scaling NOSSDAV 05
• This work
• Combines Temporal Scaling and Quality Scaling

3
Outline

• Introduction
• Model ?
• Streaming Bitrate (cost)
• Video Quality (benefit)
• Algorithm
• Experiments
• Conclusions

4
System Layers and Parameters
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Streaming Bitrate

• Total streaming bitrate, including video packets
  and FEC packets
• where G is the constant GOP rate
• NPD and NBD are the numbers of transmitting P and
  B frames depending on Temporal Scaling level lTS

6
Video Quality - Overview

• Two distortion factors
• Frame Loss
• Caused by Temporal Scaling and network packet
  loss
• Appears jerky in the video playout
• Measured by Playable Frame Rate
• Quantization Distortion
• Caused by a high quantization value with Quality
  Scaling
• Appears visually as coarse granularity in every
  frame
• Measured by ITS-VQM
• Overall Quality
• Distorted Playable Frame Rate

Wu 05 TOMCCAP
Pinson 04
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Playable Frame Rate (R)

• Frame Successful Transmission Probability
• Where Frame Size
• Frame Dependencies
• Total Playable Frame Rate

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Distorted Playable Frame Rate (RD )

• Quality scaling distortion varies exponentially
  with the quantization level
• Distorted Playable Frame Rate

Frossard 01
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Algorithm

• For each Repair and Scaling combination
• Estimate video frame sizes (SI, SP, SB)
• Compute streaming bitrate B and make sure its
  under capacity constraint T
• Use frame sizes and FEC amount to get
  successfully frame transmission rate (qI, qP, qB)
• Compute playable frame rate (R)
• Estimate quality scaling distortion (D)
• Compute distorted playable frame rate (RD)
• Exhaustively search all FEC and Scaling
  combination and look for the optimal quality

10
Outline

• Introduction
• Model
• Algorithm
• Experiments ?
• Conclusions

11
Methodology

• Built a function RD()
• Returns the distorted playable frame rate
• Built an optimization program
• TCP-Friendly Bitrate Constraint (T)
• Searches repair and scaling levels for the
  highest RD
• Compared three scaling choices with Adjusted FEC
• Temporal Scaling
• Quality Scaling
• Temporal Scaling Quality Scaling
• Compared four FEC choices with the combination of
  Temporal Scaling and Quality Scaling
• Non-FEC
• Small Fixed FEC
• Large Fixed FEC
• Adjusted FEC

12
System Setting

• GOP IBBPBBPBBPBBPBB

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Scaling Comparison with Adjusted FEC
Low Motion High Motion
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FEC Comparison with TSQS
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Conclusions

• Summary
• Derives analytical models for streaming video
  with Temporal plus Quality Scaling and FEC
• Uses OR algorithm to optimize the quality
• Compares scaling methods and FEC methods
• Conclusions
• Quality Scaling is more effective than Temporal
  Scaling
• But when bandwidth is low and network loss is
  high, Quality Scaling should be used with
  Temporal Scaling
• Motion matters
• Adjusting FEC improves video streaming quality
  significantly
• Better than fixed FEC and non-FEC

16
On Combining Temporal Scaling and Quality
Scaling for Streaming MPEG
Huahui Wu, Mark Claypool, Robert Kinicki
Computer Science, Worcester Polytechnic
Institute
Questions?