2020
DOI: 10.1007/s11042-020-09704-w
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Modeling and estimating the subjects’ diversity of opinions in video quality assessment: a neural network based approach

Abstract: Subjective experiments are considered the most reliable way to assess the perceived visual quality. However, observers’ opinions are characterized by large diversity: in fact, even the same observer is often not able to exactly repeat his first opinion when rating again a given stimulus. This makes the Mean Opinion Score (MOS) alone, in many cases, not sufficient to get accurate information about the perceived visual quality. To this aim, it is important to have a measure characterizing to what extent the obse… Show more

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Cited by 6 publications
(1 citation statement)
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“…Even without the addition of synthetic noise, the ratings in these datasets exhibit some level of noise due to inherent subject inconsistency. For example, in [34], the authors identified a processed video sequence (PVS) in the Netflix public dataset where a subject rated the quality as Bad, while the mode of the ratings for that PVS was Excellent. With respect to stimuli in the ITS4S dataset, the same authors identified a PVS where subjects uniformly chose opinion scores ranging from Poor to Excellent.…”
Section: E Assessing the Uncertainty On The Estimated Subjective Qualitymentioning
confidence: 99%
“…Even without the addition of synthetic noise, the ratings in these datasets exhibit some level of noise due to inherent subject inconsistency. For example, in [34], the authors identified a processed video sequence (PVS) in the Netflix public dataset where a subject rated the quality as Bad, while the mode of the ratings for that PVS was Excellent. With respect to stimuli in the ITS4S dataset, the same authors identified a PVS where subjects uniformly chose opinion scores ranging from Poor to Excellent.…”
Section: E Assessing the Uncertainty On The Estimated Subjective Qualitymentioning
confidence: 99%