Publication Details

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

HYNEK, J.; HRUŠKA, T. Application of Object-Based Metrics for Recognition of Well-Designed Dashboards. INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION, 2018, vol. 35, no. 13, p. 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
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 INC
Place
Philadelphia
DOI
UT WoS
000472742500007
EID Scopus
BibTeX
@article{BUT155094,
  author="Jiří {Hynek} and Tomáš {Hruška}",
  title="Application of Object-Based Metrics for Recognition of Well-Designed Dashboards",
  journal="INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION",
  year="2018",
  volume="35",
  number="13",
  pages="1203--1215",
  doi="10.1080/10447318.2018.1518004",
  issn="1044-7318",
  url="https://www.fit.vut.cz/research/publication/11827/"
}
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