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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

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

ACM MM’11

Presenter: Piggy

Date: 2012.05.07

outline
Outline
  • Introduction
  • Related Work
  • User Study
  • Result
  • Discussion and Conclusion
introduction
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
introduction1
Introduction
  • However……
    • Low video bitrate => poor video quality
  • Fortunately……
    • Nonlinear relationship between perceived quality and video bitrate
introduction2
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
introduction3
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
related work
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
related work1
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
related work2
Related Work
  • Subjective assessment
    • ITU recommendation: scale-based subjective assessment
      • 5/9/11-sclaes
      • Overburdens participants
    • Binary choice method for assessing acceptability
related work3
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)
user study
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
user study1
User Study
  • Test material - 5 content types
    • News, music, animation, sports and movie
user study2
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
user study3
User Study
  • Total 150 test clips
    • 30x5
user study4
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
user study5
User Study
  • Participants’ profile
user study6
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
user study7
User Study
  • Customized iPhone application
    • Participant profile collection
    • Content type choice
    • History review
    • Quality adjustment
      • Ascending
      • Descending
user study10
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?
result
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
acceptability and encoding parameters
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
acceptability and encoding parameters2
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
acceptability and encoding parameters3
Acceptability and Encoding Parameters
  • Bitrate-acceptability curves
acceptability and encoding parameters4
Acceptability and Encoding Parameters
  • Bitrate-acceptability curves
acceptability and encoding parameters5
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
influencing factors on quality acceptability
Influencing factors on quality Acceptability
  • Significant factors
    • Quantization parameter
    • Spatial resolution
    • Frame rate
    • Content type
    • Gender
    • Frequency
    • Duration
    • Viewing order
  • Non-significant factors
    • Age
influencing factors on quality acceptability1
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
influencing factors on quality acceptability2
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
influencing factors on quality acceptability4
Influencing factors on quality Acceptability
  • Effect of user profile
    • Gender vs. frequency
influencing factors on quality acceptability5
Influencing factors on quality Acceptability
  • Effect of user profile
    • duration vs. frequency
influencing factors on quality acceptability6
Influencing factors on quality Acceptability
  • Effect of user profile
    • Users’ preference
quality selection patterns
Quality selection patterns
  • Average time spent on switching is different from content type to content type
    • News is the lowest
quality selection patterns1
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
criteria of acceptability quality
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
discussion and conclusion
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
the end
The End
  • Thanks for your attention
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