Modeling Just Noticeable Differences in Charts

Cite This

Files in this item

Files Size Format View

There are no files associated with this item.

LU, Min, Joel LANIR, Chufeng WANG, Yucong YAO, Wen ZHANG, Oliver DEUSSEN, Hui HUANG, 2022. Modeling Just Noticeable Differences in Charts. In: IEEE Transactions on Visualization and Computer Graphics. IEEE. 28(1), pp. 718-726. ISSN 1077-2626. eISSN 1941-0506. Available under: doi: 10.1109/TVCG.2021.3114874

@article{Lu2022-01Model-55248, title={Modeling Just Noticeable Differences in Charts}, year={2022}, doi={10.1109/TVCG.2021.3114874}, number={1}, volume={28}, issn={1077-2626}, journal={IEEE Transactions on Visualization and Computer Graphics}, pages={718--726}, author={Lu, Min and Lanir, Joel and Wang, Chufeng and Yao, Yucong and Zhang, Wen and Deussen, Oliver and Huang, Hui} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:contributor>Yao, Yucong</dc:contributor> <dspace:isPartOfCollection rdf:resource=""/> <dc:creator>Wang, Chufeng</dc:creator> <dc:contributor>Wang, Chufeng</dc:contributor> <dc:creator>Zhang, Wen</dc:creator> <dcterms:abstract xml:lang="eng">One of the fundamental tasks in visualization is to compare two or more visual elements. However, it is often difficult to visually differentiate graphical elements encoding a small difference in value, such as the heights of similar bars in bar chart or angles of similar sections in pie chart. Perceptual laws can be used in order to model when and how we perceive this difference. In this work, we model the perception of Just Noticeable Differences (JNDs), the minimum difference in visual attributes that allow faithfully comparing similar elements, in charts. Specifically, we explore the relation between JNDs and two major visual variables: the intensity of visual elements and the distance between them, and study it in three charts: bar chart, pie chart and bubble chart. Through an empirical study, we identify main effects on JND for distance in bar charts, intensity in pie charts, and both distance and intensity in bubble charts. By fitting a linear mixed effects model, we model JND and find that JND grows as the exponential function of variables. We highlight several usage scenarios that make use of the JND modeling in which elements below the fitted JND are detected and enhanced with secondary visual cues for better discrimination.</dcterms:abstract> <dc:contributor>Lanir, Joel</dc:contributor> <dc:contributor>Lu, Min</dc:contributor> <dc:creator>Deussen, Oliver</dc:creator> <dcterms:issued>2022-01</dcterms:issued> <dc:date rdf:datatype="">2021-10-14T08:38:43Z</dc:date> <dcterms:isPartOf rdf:resource=""/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:contributor>Huang, Hui</dc:contributor> <dc:contributor>Zhang, Wen</dc:contributor> <dc:rights>terms-of-use</dc:rights> <dc:creator>Lu, Min</dc:creator> <dcterms:available rdf:datatype="">2021-10-14T08:38:43Z</dcterms:available> <dc:language>eng</dc:language> <dc:creator>Lanir, Joel</dc:creator> <dcterms:title>Modeling Just Noticeable Differences in Charts</dcterms:title> <bibo:uri rdf:resource=""/> <dc:creator>Huang, Hui</dc:creator> <dc:creator>Yao, Yucong</dc:creator> <dc:contributor>Deussen, Oliver</dc:contributor> <dcterms:rights rdf:resource=""/> </rdf:Description> </rdf:RDF>

This item appears in the following Collection(s)

Search KOPS


My Account