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Saving bitrate vs. pleasing users: where is the break-even point in mobile video quality?

Published: 28 November 2011 Publication History

Abstract

This paper presents a comprehensive study to find the most efficient bitrate requirement to deliver mobile video that optimizes bandwidth, while at the same time maintains good user viewing experience. In the study, forty participants were asked to choose the lowest quality video that would still provide for a comfortable and long-term viewing experience, knowing that higher video quality is more expensive and bandwidth intensive. This paper proposes the lowest pleasing bitrates and corresponding encoding parameters for five different content types: cartoon, movie, music, news and sports. It also explores how the lowest pleasing quality is influenced by content type, image resolution, bitrate, and user gender, prior viewing experience, and preference. In addition, it analyzes the trajectory of users' progression while selecting the lowest pleasing quality. The findings reveal that the lowest bitrate requirement for a pleasing viewing experience is much higher than that of the lowest acceptable quality. Users' criteria for the lowest pleasing video quality are related to the video's content features, as well as its usage purpose and the user's personal preferences. These findings can provide video providers guidance on what quality they should offer to please mobile users.

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    cover image ACM Conferences
    MM '11: Proceedings of the 19th ACM international conference on Multimedia
    November 2011
    944 pages
    ISBN:9781450306164
    DOI:10.1145/2072298
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 28 November 2011

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    Author Tags

    1. acceptability
    2. bitrate
    3. content type
    4. encoding parameters
    5. mobile video
    6. user profile

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    MM '11: ACM Multimedia Conference
    November 28 - December 1, 2011
    Arizona, Scottsdale, USA

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    Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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    • (2021)Dynamic Backlight Scaling Considering Ambient Luminance for Mobile Videos on LCD DisplaysIEEE Transactions on Mobile Computing10.1109/TMC.2020.3004534(1-1)Online publication date: 2021
    • (2020)Watching the Watchers: Resource-Efficient Mobile Video Decoding through Context-Aware Resolution AdaptationMobiQuitous 2020 - 17th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services10.1145/3448891.3448948(168-176)Online publication date: 7-Dec-2020
    • (2019)Talking Video HeadsProceedings of the 27th ACM International Conference on Multimedia10.1145/3343031.3351045(2449-2458)Online publication date: 15-Oct-2019
    • (2019)AutoTune: Game-Based Adaptive Bitrate Streaming in Cloud-Based Hybrid VoD SystemsIEEE Transactions on Services Computing10.1109/TSC.2016.260508212:4(519-533)Online publication date: 1-Jul-2019
    • (2019)AccAnn: A New Subjective Assessment Methodology for Measuring Acceptability and Annoyance of Quality of ExperienceIEEE Transactions on Multimedia10.1109/TMM.2019.290372221:10(2589-2602)Online publication date: Oct-2019
    • (2018)A Cost-Constrained Video Quality Satisfaction Study on Mobile DevicesIEEE Transactions on Multimedia10.1109/TMM.2017.276432920:5(1154-1168)Online publication date: May-2018
    • (2018)CrowdDBS: A Crowdsourced Brightness Scaling Optimization for Display Energy Reduction in Mobile VideoIEEE Transactions on Mobile Computing10.1109/TMC.2018.281285217:11(2536-2549)Online publication date: 1-Nov-2018
    • (2018)HotDASH: Hotspot Aware Adaptive Video Streaming Using Deep Reinforcement Learning2018 IEEE 26th International Conference on Network Protocols (ICNP)10.1109/ICNP.2018.00026(165-175)Online publication date: Sep-2018
    • (2017)QoE-Driven Efficient Resource Utilisation for Video Over Critical Communication SystemsMultimedia Services and Applications in Mission Critical Communication Systems10.4018/978-1-5225-2113-6.ch008(168-187)Online publication date: 2017
    • (2017)Rethinking HTTP Adaptive Streaming with the Mobile User PerceptionProceedings of the 25th ACM international conference on Multimedia10.1145/3123266.3123357(925-933)Online publication date: 23-Oct-2017
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