Understanding the Impact of Referent Design on Scale Perception in Immersive Data Visualization
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866914726421725184 |
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| author | Hou, Yihan Cui, Hao Chen, Rongrong Zeng, Wei |
| author_facet | Hou, Yihan Cui, Hao Chen, Rongrong Zeng, Wei |
| contents | Referents are often used to enhance scale perception in immersive visualizations. Common referent designs include the considerations of referent layout (side-by-side vs. in-situ) and referent size (small vs. medium vs. large). This paper introduces a controlled user study to assess how different referent designs affect the efficiency and accuracy of scale perception across different data scales, on the performance of the size-matching task in the virtual environment. Our results reveal that in-situ layouts significantly enhance accuracy and confidence across various data scales, particularly with large referents. Linear regression analyses further confirm that in-situ layouts exhibit greater resilience to changes in data scale. For tasks requiring efficiency, medium-sized referents emerge as the preferred choice. Based on these findings, we offer design guidelines for selecting referent layouts and sizes in immersive visualizations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_16018 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Understanding the Impact of Referent Design on Scale Perception in Immersive Data Visualization Hou, Yihan Cui, Hao Chen, Rongrong Zeng, Wei Human-Computer Interaction Referents are often used to enhance scale perception in immersive visualizations. Common referent designs include the considerations of referent layout (side-by-side vs. in-situ) and referent size (small vs. medium vs. large). This paper introduces a controlled user study to assess how different referent designs affect the efficiency and accuracy of scale perception across different data scales, on the performance of the size-matching task in the virtual environment. Our results reveal that in-situ layouts significantly enhance accuracy and confidence across various data scales, particularly with large referents. Linear regression analyses further confirm that in-situ layouts exhibit greater resilience to changes in data scale. For tasks requiring efficiency, medium-sized referents emerge as the preferred choice. Based on these findings, we offer design guidelines for selecting referent layouts and sizes in immersive visualizations. |
| title | Understanding the Impact of Referent Design on Scale Perception in Immersive Data Visualization |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2403.16018 |