Video Quality Measurement based on Network Traffic

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The document presents research on measuring video quality based on network traffic. It proposes using both application and network level metrics to estimate distortion and quality. At the application level, motion intensity is measured using I, P, and B frame sizes. At the network level, packet loss effects are estimated based on GOP properties and structure. Distortion is estimated as the product of motion intensity and loss effect, and quality is estimated as 1 minus the distortion. The research was evaluated using software like VLC and QPSNR, and results were validated by comparing to other quality metrics and calculating the coefficient of variation and RMSE for different packet error rates. Benefits of the approach include simplicity, minimal overhead, online evaluation, non-reference nature, and

Internet

Video Quality Measurement
based on Network Traffic
Researcher: Amir Hossein Mandegar
Supervisor: Dr. Behzad Akbari
Adviser: Dr. Hadi Sargolzayie
March 2012
Computer Engineering and IT Department

Video Quality Measurement based on Network Traffic 2
Outline
 Introduction
 Application Metric
 Network Metric
 Distortion Estimation
 Conclusion

Video Quality Measurement based on Network Traffic 3
Introduction
 User Perceptual Quality Measurement Necessity
 Video Stream Quality Measurement
 Subjective (DSCQS, DSIS, SSCQE, ACR, ...)
 Objective (PSNR, SSIM, VQM, ...)
 Passive Measurement (Intercept and Analysis)
 Proposed Metrics (Distortion)
 Application Level Metric
 Network Level Metric

Video Quality Measurement based on Network Traffic 4
Outline
 Introduction
 Application Metric
 Network Metric
 Distortion Estimation
 Conclusion

Video Quality Measurement based on Network Traffic 5
Creator:cairo 1.10.2 (http://cairographi
CreationDate:Wed Jan 25 15:38:56 2012
LanguageLevel:2
Application Level Metric
 Video Motion Intensity
 Frame I:
 Independent, Valuable, Large Size
 Frame P:
 Relative, Valuable, Medium Size (P != 0 & I)

Video Quality Measurement based on Network Traffic 6
Title:plot_div_2.eps
Creator:gnuplot 4.4 patchlevel 0
CreationDate:Wed Jan 25 12:11:07 2012
Application Level Metric
 Motion Intensity Motion Intensity=
Pframesize
Iframesize

Video Quality Measurement based on Network Traffic 7
Outline
 Introduction
 Application Metric
 Network Metric
 Distortion Estimation
 Conclusion

Video Quality Measurement based on Network Traffic 8
Network Level Metric
 Packet Loss Effect
 GOP Properties and Structure Detection
 GOP Loss Measurement (gap detection)
eloss=
PI ×EI ×Losspkt +
PP×E P×Losspkt +
PB×EB×Losspkt
Px=
framexpkt
GOP pkt

Video Quality Measurement based on Network Traffic 9
Creator:cairo 1.10.2 (http://cairographi
CreationDate:Wed Jan 25 15:38:15 2012
LanguageLevel:2
Network Level Metric
 Frame Effect
EI =I qtyPqtyBqty
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Video Quality Measurement based on Network Traffic 10
Title:plot.loss.w.eps
Creator:gnuplot 4.4 patchlevel 0
CreationDate:Wed Jan 25 12:46:15 2012
Network Level Metric
 Loss Effect (I,P,B – 1, 6, 10)
Loss Effect=
eLoss
GOP pkt

Video Quality Measurement based on Network Traffic 11
Outline
 Introduction
 Application Metric
 Network Metric
 Distortion Estimation
 Conclusion

Video Quality Measurement based on Network Traffic 12
Distortion Estimation
DistortionEstimation=Motion Intensity×Loss Effect
Quality Estimation=1−Distortion Estimation
Title:plot.loss.w.s.eps
Creator:gnuplot 4.4 patchlevel 0
CreationDate:Wed Jan 25 12:56:52 2012

Video Quality Measurement based on Network Traffic 13
Outline
 Introduction
 Application Metric
 Network Metric
 Distortion Estimation
 Conclusion

Video Quality Measurement based on Network Traffic 14
Conclusion - Evaluation
 RTSP / RTP / RTP Payload(rfc2250)
 Qt Development Platform
 CORE Emulator
 VLC Video Server
 MPlayer
 QPSNR
 GNUPlot
 Bash- AWK
Title:/home/archive/University/89-2_90
Creator:Dia v0.97.1
CreationDate:Wed Jan 25 16:39:43 2012

Video Quality Measurement based on Network Traffic 15
Title:plot-5.eps
Creator:gnuplot 4.4 patchlevel 0
CreationDate:Wed Jan 25 13:15:04 2012
Conclusion - Validation
 Result Comparison (PER = 5%)

Video Quality Measurement based on Network Traffic 16
Conclusion - Validation
 Coefficient of Variation
 RMSE
c.v.=


RMSE x1, x2=
∑i=1
n
 x1,i−x2,i
2
n
PER Akiyo Coastguard Football
1% 6.02079e-05 0.00315822 0.0538926
2% 0.00167713 0.0674445 0.0444743
5% 0.000324692 0.06919 0.110896
10% 0.00210861 0.066475 0.100087

Video Quality Measurement based on Network Traffic 17
Conclusion - Benefits/Future
 Simplicity
 Minimum Calculation Overhead
 Online Evaluation (Stream-Based)
 Non-Reference
 Suitable Accuracy
 Exact Frame Packet Loss / NeuroFuzzy
Paper:
A Video Streaming Quality Assessment Scheme
Based on Packet Level Measurement

Acknowledgment
and Question !
Appreciate to:
Dr. Mousakhani President of QIAU
Dr. Behzad Akbari my Valuable Supervisor
Dr.Sargolzayie & Dr.Ghasemi
Supportive and Patient`s Wife and Family

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Video Quality Measurement based on Network Traffic

1. Video Quality Measurement based on Network Traffic Researcher: Amir Hossein Mandegar Supervisor: Dr. Behzad Akbari Adviser: Dr. Hadi Sargolzayie March 2012 Computer Engineering and IT Department

2. Video Quality Measurement based on Network Traffic 2 Outline  Introduction  Application Metric  Network Metric  Distortion Estimation  Conclusion

3. Video Quality Measurement based on Network Traffic 3 Introduction  User Perceptual Quality Measurement Necessity  Video Stream Quality Measurement  Subjective (DSCQS, DSIS, SSCQE, ACR, ...)  Objective (PSNR, SSIM, VQM, ...)  Passive Measurement (Intercept and Analysis)  Proposed Metrics (Distortion)  Application Level Metric  Network Level Metric

4. Video Quality Measurement based on Network Traffic 4 Outline  Introduction  Application Metric  Network Metric  Distortion Estimation  Conclusion

5. Video Quality Measurement based on Network Traffic 5 Creator:cairo 1.10.2 (http://cairographi CreationDate:Wed Jan 25 15:38:56 2012 LanguageLevel:2 Application Level Metric  Video Motion Intensity  Frame I:  Independent, Valuable, Large Size  Frame P:  Relative, Valuable, Medium Size (P != 0 & I)

6. Video Quality Measurement based on Network Traffic 6 Title:plot_div_2.eps Creator:gnuplot 4.4 patchlevel 0 CreationDate:Wed Jan 25 12:11:07 2012 Application Level Metric  Motion Intensity Motion Intensity= Pframesize Iframesize

7. Video Quality Measurement based on Network Traffic 7 Outline  Introduction  Application Metric  Network Metric  Distortion Estimation  Conclusion

8. Video Quality Measurement based on Network Traffic 8 Network Level Metric  Packet Loss Effect  GOP Properties and Structure Detection  GOP Loss Measurement (gap detection) eloss= PI ×EI ×Losspkt + PP×E P×Losspkt + PB×EB×Losspkt Px= framexpkt GOP pkt

9. Video Quality Measurement based on Network Traffic 9 Creator:cairo 1.10.2 (http://cairographi CreationDate:Wed Jan 25 15:38:15 2012 LanguageLevel:2 Network Level Metric  Frame Effect EI =I qtyPqtyBqty EP= ∑i=i Pqty EB1×i Pqty EB= Bqty Pqty1

10. Video Quality Measurement based on Network Traffic 10 Title:plot.loss.w.eps Creator:gnuplot 4.4 patchlevel 0 CreationDate:Wed Jan 25 12:46:15 2012 Network Level Metric  Loss Effect (I,P,B – 1, 6, 10) Loss Effect= eLoss GOP pkt

11. Video Quality Measurement based on Network Traffic 11 Outline  Introduction  Application Metric  Network Metric  Distortion Estimation  Conclusion

12. Video Quality Measurement based on Network Traffic 12 Distortion Estimation DistortionEstimation=Motion Intensity×Loss Effect Quality Estimation=1−Distortion Estimation Title:plot.loss.w.s.eps Creator:gnuplot 4.4 patchlevel 0 CreationDate:Wed Jan 25 12:56:52 2012

13. Video Quality Measurement based on Network Traffic 13 Outline  Introduction  Application Metric  Network Metric  Distortion Estimation  Conclusion

14. Video Quality Measurement based on Network Traffic 14 Conclusion - Evaluation  RTSP / RTP / RTP Payload(rfc2250)  Qt Development Platform  CORE Emulator  VLC Video Server  MPlayer  QPSNR  GNUPlot  Bash- AWK Title:/home/archive/University/89-2_90 Creator:Dia v0.97.1 CreationDate:Wed Jan 25 16:39:43 2012

15. Video Quality Measurement based on Network Traffic 15 Title:plot-5.eps Creator:gnuplot 4.4 patchlevel 0 CreationDate:Wed Jan 25 13:15:04 2012 Conclusion - Validation  Result Comparison (PER = 5%)

16. Video Quality Measurement based on Network Traffic 16 Conclusion - Validation  Coefficient of Variation  RMSE c.v.=   RMSE x1, x2= ∑i=1 n  x1,i−x2,i 2 n PER Akiyo Coastguard Football 1% 6.02079e-05 0.00315822 0.0538926 2% 0.00167713 0.0674445 0.0444743 5% 0.000324692 0.06919 0.110896 10% 0.00210861 0.066475 0.100087

17. Video Quality Measurement based on Network Traffic 17 Conclusion - Benefits/Future  Simplicity  Minimum Calculation Overhead  Online Evaluation (Stream-Based)  Non-Reference  Suitable Accuracy  Exact Frame Packet Loss / NeuroFuzzy Paper: A Video Streaming Quality Assessment Scheme Based on Packet Level Measurement

18. Acknowledgment and Question ! Appreciate to: Dr. Mousakhani President of QIAU Dr. Behzad Akbari my Valuable Supervisor Dr.Sargolzayie & Dr.Ghasemi Supportive and Patient`s Wife and Family

Video Quality Measurement based on Network Traffic

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