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Saving Bitrate vs. Users: Where is the Break-Even Point in Mobile Video Quality?

Saving Bitrate vs. Users: Where is the Break-Even Point in Mobile Video Quality?. ACM MM’11 Presenter: Piggy Date: 2012.05.07. Outline. Introduction Related Work User Study Result Discussion and Conclusion. Introduction. Mobile video service is getting popular

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Saving Bitrate vs. Users: Where is the Break-Even Point in Mobile Video Quality?

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  1. Saving Bitrate vs. Users: Where is the Break-Even Point in Mobile Video Quality? ACM MM’11 Presenter: Piggy Date: 2012.05.07

  2. Outline • Introduction • Related Work • User Study • Result • Discussion and Conclusion

  3. Introduction • Mobile video service is getting popular • Due to the development of mobile device • Minimizing video bitrate is important • Wireless networks prefer low bitrate to adapt to different bandwidth conditions • Users prefer low bitrate as most network providers normally charge for data usage • Video providers need to save costs associated with serving the content

  4. Introduction • However…… • Low video bitrate => poor video quality • Fortunately…… • Nonlinear relationship between perceived quality and video bitrate

  5. Introduction • Goal: To find the most efficient bitrate requirement that • Optimizes bandwidth usage • Maintains good user viewing experience • Lowest acceptable video quality vs. lowest quality for long term viewing

  6. Introduction • Contribution • Mapping of video bitrates to the subjective judgment of quality pleasantness • Impact of content type, video encoding parameters and user profile on mobile video viewing experience • Users’ selection processes and their criteria for the lowest pleasing quality for different content type

  7. Related Work • Users’ requirements for mobile video depends on • Social and psychological factors • Consumption model, service, user profile, context, etc… • Video quality • Spatial and temporal resolution • Quantization • Motion and texture complexity

  8. Related Work • Factors influence the reduction of bitrate • Resolution • Frame rate • Quantization • And the degradation in perceived video quality is not proportionate to the decrease in bitrate

  9. Related Work • Subjective assessment • ITU recommendation: scale-based subjective assessment • 5/9/11-sclaes • Overburdens participants • Binary choice method for assessing acceptability

  10. Related Work • Though previous works have identified the lowest acceptable quality level • They were restricted by the technology and device at that time. • Different resolution • People behaviors have changed (got used to HD quality)

  11. User Study • Equipment • iPhone 3GS with 16GB storage • Display: 480x320 pixels • H.264/AVC • Up to 1.5 Mbps, 640x480 pixels, and 30 frames per second • AAC-LC audio format • Up to 150 kbps, 48kHz

  12. User Study • Test material - 5 content types • News, music, animation, sports and movie

  13. User Study • Test material – encoding using 3 parameters • Quantization parameters (QP) • Spatial resolution (SR) • 320x240, 480x320, and 640x480 • Frame rate (FR) • Divided into 3 groups based on SR:L, M and H with each group contain 10 test clips • 30 test clips for each content type

  14. User Study • Total 150 test clips • 30x5

  15. User Study • Participants • Lounge area outside of a university library • 40 participants • Equal number of males and females • Age range: 17 ~ 35 (average = 23.2) • User profile collection • Experience of using mobile video • Preference for content types

  16. User Study • Participants’ profile

  17. User Study • Procedure • Scenario explanation • 3 steps within 20-25 mins for data collection • Participant’s profile collection • Participant randomly chose the video contents • A short interview

  18. User Study • Customized iPhone application • Participant profile collection • Content type choice • History review • Quality adjustment • Ascending • Descending

  19. User Study

  20. User Study

  21. User Study • Interview • What criteria did you use to select the desired video quality? • Is there any difference between your criteria for different content type? Why?

  22. Result • Acceptability calculation • Lower than the selected lowest acceptable clip => 0 • Otherwise => 1 • Refers to the percentage of participants accepting a video quality as the lowest quality • Binary Logistic Regression • Video encoding parameters • Content type • Viewing order • User profile

  23. Acceptability and Encoding Parameters • Different from • Content to content • Resolution to resolution • Movie is the lowest while new is the highest • The difference reduces as the resolution increases

  24. Acceptability and Encoding Parameters

  25. Acceptability and Encoding Parameters • Acceptability group • 0 – 40% should be avoided • 41 – 60% critical state • 61 – 80% can please users • 81 – 100% high user satisfaction

  26. Acceptability and Encoding Parameters • Bitrate-acceptability curves

  27. Acceptability and Encoding Parameters • Bitrate-acceptability curves

  28. Acceptability and Encoding Parameters • Bitrate-acceptability curves • High resolution needs a higher bitrate • The acceptability of “sport” rises slower than other content types • Mapping of bitrate to acceptability

  29. Influencing factors on quality Acceptability • Significant factors • Quantization parameter • Spatial resolution • Frame rate • Content type • Gender • Frequency • Duration • Viewing order • Non-significant factors • Age

  30. Influencing factors on quality Acceptability • Effect of content type • Movie vs. music, news, and animation • Spatial resolution decreases => content type more significant • Effect of encoding parameters • Video quality increases with • Decrease of QP (great difference among adjacent QP values) • Increase of SR • Increase of FR

  31. Influencing factors on quality Acceptability • Effect of viewing order • Acceptability in descending order is lower than ascending order • Significant for animation, music, news and sports but not for movie

  32. Influencing factors on quality Acceptability • Effect of user profile

  33. Influencing factors on quality Acceptability • Effect of user profile • Gender vs. frequency

  34. Influencing factors on quality Acceptability • Effect of user profile • duration vs. frequency

  35. Influencing factors on quality Acceptability • Effect of user profile • Users’ preference

  36. Quality selection patterns • Average time spent on switching is different from content type to content type • News is the lowest

  37. Quality selection patterns • Two selection patterns • Directly choose the target qualities without hesitation – mostly in ascending order • Bounced to and from the lower of higher quality for comparison – mostly in descending order

  38. Criteria of acceptability quality • Users have different assessment criteria for different content types • Movie – high quality required (HD quality) • News – audio quality and sync. • Music – audio quality • Animation – fewer requirement • Sport – higher quality needed when small objects appear • Users’ preference leads to different result on the same content type • Ex: sport and news

  39. Discussion and Conclusion • Users’ profile matters • The result is different from previous works • Exact required bitrate still depends on individual video, here only gives a estimated range • Platform dependency as well as video codecs • Fixed vs. adjustable service? • Prediction model and optimal delivery strategy

  40. The End • Thanks for your attention

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