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Article

Affective Colormap Design for Accurate Visual Comprehension in Industrial Tomography

1
Department of Computer Science and Engineering, Chalmers University of Technology, SE-41296 Gothenburg, Sweden
2
Department of Applied Information Technology, University of Gothenburg, SE-40530 Gothenburg, Sweden
3
Department of Computer Science, National University of Singapore, Singapore 119077, Singapore
*
Author to whom correspondence should be addressed.
This paper is an extension version of the conference paper: Zhang, Y.; Fjeld, M.; Said, A.; Fratarcangeli, M. Task-based Colormap Design Supporting Visual Comprehension in Process Tomography. In Proceedings of the EuroVis 2020, Norrköping, Sweden, 25–29 May 2020.
Academic Editor: Jochen Lang
Sensors 2021, 21(14), 4766; https://doi.org/10.3390/s21144766
Received: 2 June 2021 / Revised: 6 July 2021 / Accepted: 8 July 2021 / Published: 12 July 2021
(This article belongs to the Section Intelligent Sensors)
The design of colormaps can help tomography operators obtain accurate visual comprehension, thereby assisting safety-critical decisions. The research presented here is about deploying colormaps that promote the best affective responses for industrial microwave tomography (MWT). To answer the two research questions related to our study, we firstly conducted a quantitative analysis of 11 frequently-used colormaps on a segmentation task. Secondly, we presented the same colormaps within a crowdsourced study comprising two parts to verify the quantitative outcomes. The first part encoded affective responses from participants into a prevailing four-quadrant valence–arousal grid; the second part recorded participant ratings towards the accuracy of each colormap on MWT segmentation. We concluded that three colormaps are the best suited in the context of MWT tasks. We also found that the colormaps triggering emotions in the positive–exciting quadrant can facilitate more accurate visual comprehension than other affect-related quadrants. A synthetic colormap design guideline was consequently proposed. View Full-Text
Keywords: affective colormap design; human perception; visualization; crowdsourced study; microwave tomography affective colormap design; human perception; visualization; crowdsourced study; microwave tomography
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MDPI and ACS Style

Zhang, Y.; Fjeld, M.; Fratarcangeli, M.; Said, A.; Zhao, S. Affective Colormap Design for Accurate Visual Comprehension in Industrial Tomography. Sensors 2021, 21, 4766. https://doi.org/10.3390/s21144766

AMA Style

Zhang Y, Fjeld M, Fratarcangeli M, Said A, Zhao S. Affective Colormap Design for Accurate Visual Comprehension in Industrial Tomography. Sensors. 2021; 21(14):4766. https://doi.org/10.3390/s21144766

Chicago/Turabian Style

Zhang, Yuchong, Morten Fjeld, Marco Fratarcangeli, Alan Said, and Shengdong Zhao. 2021. "Affective Colormap Design for Accurate Visual Comprehension in Industrial Tomography" Sensors 21, no. 14: 4766. https://doi.org/10.3390/s21144766

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