Using perceptual strength estimates to predict the perceived annoyance of videos with combinations of spatial and temporal artifacts

Alexandre Fieno Silva; Mylène C. Q. Farias

doi:10.1117/1.JEI.27.4.043018

20 July 2018 Using perceptual strength estimates to predict the perceived annoyance of videos with combinations of spatial and temporal artifacts

Alexandre Fieno Silva, Mylène C. Q. Farias

Author Affiliations +

Journal of Electronic Imaging, Vol. 27, Issue 4, 043018 (July 2018). https://doi.org/10.1117/1.JEI.27.4.043018

Abstract

We report the results of a set of psychophysical experiments that measure the perceptual strengths of videos with different combinations of blockiness, blurriness, and packet-loss artifacts. Participants were instructed to search each video for impairments and rate the strength of their individual features (artifacts). A repeated-measure analysis of variance (RM-ANOVA) performed on the data showed that artifact physical strengths have a significant effect on annoyance judgments. We tested a weighted Minkowski model, a support vector regression model, and a linear model on the experimental data. We found that all these models give a good description of the relation between individual artifact perceptual strengths and the overall annoyance. In the other words, all models presented a very good correlation with the experimental data, showing that annoyance can be modeled as a multidimensional function of the individual artifact perceptual strengths. Additionally, results show that there are interactions among artifact signals.

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Alexandre Fieno Silva and Mylène C. Q. Farias "Using perceptual strength estimates to predict the perceived annoyance of videos with combinations of spatial and temporal artifacts," Journal of Electronic Imaging 27(4), 043018 (20 July 2018). https://doi.org/10.1117/1.JEI.27.4.043018

Received: 17 December 2017; Accepted: 5 June 2018; Published: 20 July 2018

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KEYWORDS

Video

Data modeling

Micro unmanned aerial vehicles

Plasma display panels

Error analysis

Statistical analysis

Performance modeling

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