From pairwise comparisons and rating to a unified quality scale.
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Authors
Hulusic, Vedad
Valenzise, Giuseppe
Publication Date
2019-08-28Journal Title
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
ISSN
1057-7149
Publisher
Institute of Electrical and Electronics Engineers
Language
eng
Type
Article
This Version
AM
Physical Medium
Print-Electronic
Metadata
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Perez-Ortiz, M., Mikhailiuk, A., Zerman, E., Hulusic, V., Valenzise, G., & Mantiuk, R. (2019). From pairwise comparisons and rating to a unified quality scale.. IEEE transactions on image processing : a publication of the IEEE Signal Processing Society https://doi.org/10.1109/tip.2019.2936103
Abstract
The goal of psychometric scaling is the quantification of perceptual experiences, understanding the relationship between an external stimulus, the internal representation and the response. In this paper, we propose a probabilistic framework to fuse the outcome of different psychophysical experimental protocols, namely rating and pairwise comparisons experiments. Such a method can be used for merging existing datasets of subjective nature and for experiments in which both measurements are collected. We analyze and compare the outcomes of both types of experimental protocols in terms of time and accuracy in a set of simulations and experiments with benchmark and realworld image quality assessment datasets, showing the necessity of scaling and the advantages of each protocol and mixing. Although most of our examples focus on image quality assessment, our findings generalize to any other subjective quality-of-experience task.
Sponsorship
This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement n◦ 725253–EyeCode), from EPSRC research grant EP/P007902/1 and from a Science Foundation Ireland (SFI) research grant under the Grant Number 15/RP/2776. Marıa Pérez-Ortiz did part of this work while at the University of Cambridge and University College London (under MURI grant EPSRC 542892).
Funder references
EPSRC (EP/P007902/1)
European Commission Horizon 2020 (H2020) ERC (725253)
Identifiers
External DOI: https://doi.org/10.1109/tip.2019.2936103
This record's URL: https://www.repository.cam.ac.uk/handle/1810/296154
Rights
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