On subjective quality assessment of adaptive video streaming via crowdsourcing and laboratory based experiments

Jacob Søgaard, Muhammad Shahid, Jeevan Pokhrel, Kjell Brunnstrom

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    Video streaming services are offered over the Internet and since the service providers do not have full control over the network conditions all the way to the end user, streaming technologies have been developed to maintain the quality of service in these varying network conditions i.e. so called adaptive video streaming. In order to cater for users' Quality of Experience (QoE) requirements, HTTP based adaptive streaming solutions of video services have become popular. However, the keys to ensure the users a good QoE with this technology is still not completely understood. User QoE feedback is therefore instrumental in improving this understanding. Controlled laboratory based perceptual quality experiments that involve a panel of human viewers are considered to be the most valid method of the assessment of QoE. Besides laboratory based subjective experiments, crowdsourcing based subjective assessment of video quality is gaining popularity as an alternative method. This article presents insights into a study that investigates perceptual preferences of various adaptive video streaming scenarios through crowdsourcing based and laboratory based subjective assessment. The major novel contribution of this study is the application of Paired Comparison based subjective assessment in a crowdsourcing environment. The obtained results provide some novel indications, besides confirming the earlier published trends, of perceptual preferences for adaptive scenarios of video streaming. Our study suggests that in a network environment with fluctuations in the bandwidth, a medium or low video bitrate which can be kept constant is the best approach. Moreover, if there are only a few drops in bandwidth, one can choose a medium or high bitrate with a single or few buffering events.
    Original languageEnglish
    JournalMultimedia Tools and Applications
    Issue number15
    Pages (from-to)16727-16748
    Number of pages22
    Publication statusPublished - 2017


    • Adaptive video streaming
    • Crowdsourcing
    • Subjective quality assessment
    • Quality of experience


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