A Framework for Simulating Subjective Experiments: Testing Subject Screening

The ITU-T recommendations BT.500 and P.910 outline multiple subject screening methodologies for subjective multimedia quality experiments. Yet, their real-world effectiveness remains difficult to verify due to the lack of known ground truth. This paper introduces a comprehensive simulation framework designed to objectively assess subject screening methods by generating synthetic subjective scores with known parameters. Two primary experimental scenarios — typical and super-precise subject models — were evaluated using simulated data. Results indicate that correlation-based screening methods (P.910) outperform kurtosis-based methods (BT.500) in detecting irrelevant subjects, thereby improving the precision of subjective experiment outcomes. Additional contributions include the development of a novel score generation model and the definition of robust evaluation metrics. We hope this paper will serve as the basis for future analysis based on simulations of subjective experiments.

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Publication Details

Journal
ACM Transactions on Multimedia Computing Communications and Applications
Published
2025-12-22
DOI
https://doi.org/10.1145/3785667
Primary Topic
Image and Video Quality Assessment
Type
article
Field-Weighted Citation Impact
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article

A Framework for Simulating Subjective Experiments: Testing Subject Screening

Irene Viola, Lucjan Janowski
ACM Transactions on Multimedia Computing Communications and Applications
Image and Video Quality Assessment
article

A Framework for Simulating Subjective Experiments: Testing Subject Screening

Irene Viola, Lucjan Janowski
article en

Abstract

The ITU-T recommendations BT.500 and P.910 outline multiple subject screening methodologies for subjective multimedia quality experiments. Yet, their real-world effectiveness remains difficult to verify due to the lack of known ground truth. This paper introduces a comprehensive simulation framework designed to objectively assess subject screening methods by generating synthetic subjective scores with known parameters. Two primary experimental scenarios — typical and super-precise subject models — were evaluated using simulated data. Results indicate that correlation-based screening methods (P.910) outperform kurtosis-based methods (BT.500) in detecting irrelevant subjects, thereby improving the precision of subjective experiment outcomes. Additional contributions include the development of a novel score generation model and the definition of robust evaluation metrics. We hope this paper will serve as the basis for future analysis based on simulations of subjective experiments.

ACM Transactions on Multimedia Computing Communications and Applications
Centrum Wiskunde & Informatica (NL), AGH University of Krakow (PL)
Openalex Percentile: Top 37%
Image and Video Quality Assessment
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