Quality Assessment of Adaptive Bitrate Videos using Image Metrics and Machine Learning

Jacob Søgaard, Søren Forchhammer, Kjell Brunnström

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Abstract

Adaptive bitrate (ABR) streaming is widely used for distribution of videos over the internet. In this work, we investigate how well we can predict the quality of such videos using well-known image metrics, information about the bitrate levels, and a relatively simple machine learning method. Quality assessment of ABR videos is a hard problem, but our initial results are promising. We obtain a Spearman rank order correlation of 0.88 using content-independent cross-validation.
Original languageEnglish
Title of host publicationProceedings of Qomex 2015
Number of pages2
PublisherIEEE
Publication date2015
ISBN (Print)978-1-4799-8958-4
DOIs
Publication statusPublished - 2015
Event7th International Workshop on Quality of Multimedia Experience - Costa Navarino, Messinia, Greece
Duration: 26 May 201529 May 2015

Conference

Conference7th International Workshop on Quality of Multimedia Experience
CountryGreece
CityCosta Navarino, Messinia
Period26/05/201529/05/2015

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