Faculty of Information Technology, BUT

Publication Details

Application of Object-Based Metrics for Recognition of Well-Designed Dashboards

HYNEK Jiří and HRUŠKA Tomáš. Application of Object-Based Metrics for Recognition of Well-Designed Dashboards. International Journal of Human-Computer Interaction, vol. 35, no. 13, pp. 1203-1215. ISSN 1044-7318.
Czech title
Aplikace metrik analyzujících objekty uživatelských rozhraní pro výběr dobře navržených vzorků nástroje dashboard
Type
journal article
Language
english
Authors
Hynek Jiří, Ing. (DIFS FIT BUT)
Hruška Tomáš, prof. Ing., CSc. (RCIT FIT BUT)
Keywords
dashboard, metric-based evaluation, objectivity, aesthetics, subjective perception
Abstract
Measuring the characteristics of visually emphasized objects displayed on a screen seems to be a promising way to rate user interface quality. On the other hand, it brings us problems regarding the ambiguity of object recognition caused by the subjective perception of the users. The goal of this research is to analyze the applicability of chosen object-based metrics for the evaluation of dashboard quality and the ability to distinguish well-design samples, with the focus on the subjective perception of the users. This article presents the model for the rating and classification of object-based metrics according to their ability to objectively distinguish well-designed dashboards. We use the model to rate 13 existing object-based metrics of aesthetics. Then, we present a new approach for the improvement of the rating of one object-based metric - Balance. We base the improvement on the combination of the object-based metric with the pixel-based analysis of color distribution on the screen.
Published
2018
Pages
1203-1215
Journal
International Journal of Human-Computer Interaction, vol. 35, no. 13, ISSN 1044-7318
Publisher
Taylor & Francis Informa plc
DOI
BibTeX
@ARTICLE{FITPUB11827,
   author = "Ji\v{r}\'{i} Hynek and Tom\'{a}\v{s} Hru\v{s}ka",
   title = "Application of Object-Based Metrics for Recognition of Well-Designed Dashboards",
   pages = "1203--1215",
   journal = "International Journal of Human-Computer Interaction",
   volume = 35,
   number = 13,
   year = 2018,
   ISSN = "1044-7318",
   doi = "10.1080/10447318.2018.1518004",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/11827"
}
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