Impact of feedback on crowdsourced visual quality assessment with paired comparisons
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This paper presents a comprehensive investigation into the effects of immediate feedback on crowdworkers’ performance in subjective image quality assessment tasks using paired comparisons. The study is motivated by the need for reliable and efficient crowdsourcing tasks for image quality assessment. A large-scale experiment involving 200 participants was conducted, where participants completed 120 paired comparisons with and without feedback. The feedback informed the workers of the correctness of their responses to comparisons. Almost all of the participants (97%) preferred receiving feedback. The results indicate that feedback reduced response time, improved user experience, and did not cause a bias in the estimation of the just noticeable difference (JND). On the other hand, feedback did not significantly affect accuracy, correlation with the ground truth, or create a learning effect. This study contributes to the field by being one of the first to examine the impact of feedback on crowdworker performance in subjective image quality assessment tasks. The dataset which includes the images and ratings can be accessed at https://database.mmsp-kn.de/feedback-study-dataset.html.
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JENADELEH, Mohsen, Alexander HESS, Simon HVIID DEL PIN, Edwin GAMBOA, Matthias HIRTH, Dietmar SAUPE, 2024. Impact of feedback on crowdsourced visual quality assessment with paired comparisons. 2024 16th International Conference on Quality of Multimedia Experience (QoMEX). Karlshamn, Sweden, 18. Juni 2024 - 20. Juni 2024. In: 16th International Conference on Quality of Multimedia Experience (QoMEX). Piscataway, NJ: IEEE, 2024, S. 125-131. ISBN 979-8-3503-6158-2. Verfügbar unter: doi: 10.1109/QoMEX61742.2024.10598256BibTex
@inproceedings{Jenadeleh2024Impac-70264, year={2024}, doi={10.1109/QoMEX61742.2024.10598256}, title={Impact of feedback on crowdsourced visual quality assessment with paired comparisons}, isbn={979-8-3503-6158-2}, publisher={IEEE}, address={Piscataway, NJ}, booktitle={16th International Conference on Quality of Multimedia Experience (QoMEX)}, pages={125--131}, author={Jenadeleh, Mohsen and Heß, Alexander and Hviid Del Pin, Simon and Gamboa, Edwin and Hirth, Matthias and Saupe, Dietmar}, note={This research is funded by the DFG (German Research Foundation) – Project ID 496858717, titled “JND-based Perceptual Video Quality Analysis and Modeling”. D.S. is funded by DFG Project ID 251654672 – TRR 161. S.H.D.P. is supported by the project “Quality and Content: understanding the influence of content on subjective and objective image quality assessment” (grant number 324663, approved on 1 October 2021) from the Research Council of Norway.} }
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