Publication detail

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

HYNEK, J. HRUŠKA, T.

Original Title

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

Type

journal article in Web of Science

Language

English

Original 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.

Keywords

dashboard, metric-based evaluation, objectivity, aesthetics, subjective perception

Authors

HYNEK, J.; HRUŠKA, T.

Released

19. 9. 2018

Publisher

TAYLOR & FRANCIS INC

Location

Philadelphia

ISBN

1044-7318

Periodical

INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION

Year of study

35

Number

13

State

United States of America

Pages from

1203

Pages to

1215

Pages count

13

URL

https://www.fit.vut.cz/research/publication/11827/

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/"
}