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Analysing the Impact of Cross-Content Pairs on Pairwise Comparison Scaling

Abstract : Pairwise comparisons (PWC) methodology is one of the most commonly used methods for subjective quality assessment, especially for computer graphics and multimedia applications. Unlike rating methods, a psychometric scaling operation is required to convert PWC results to numerical subjective quality values. Due to the nature of this scaling operation, the obtained quality scores are relative to the set they are computed in. While it is customary to compare different versions of the same content, in this work we study how cross-content comparisons may benefit psychometric scaling. For this purpose, we use two different video quality databases which have both rating and PWC experiment results. The results show that despite same-content comparisons play a major role in the accuracy of psychometric scaling, the use of a small portion of cross-content comparison pairs is indeed beneficial to obtain more accurate quality estimates.
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Contributor : Giuseppe Valenzise <>
Submitted on : Friday, February 26, 2021 - 11:27:47 AM
Last modification on : Friday, April 30, 2021 - 10:05:29 AM
Long-term archiving on: : Thursday, May 27, 2021 - 6:03:56 PM


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Emin Zerman, Giuseppe Valenzise, Aljosa Smolic. Analysing the Impact of Cross-Content Pairs on Pairwise Comparison Scaling. 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX), Jun 2019, Berlin, Germany. pp.1-6, ⟨10.1109/QoMEX.2019.8743295⟩. ⟨hal-02400483⟩



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