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Computation of Pixel-Oriented Grid Layout for 2D Datasets Using VRGrid

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Artificial Intelligence and Visualization: Advancing Visual Knowledge Discovery

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1126))

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Abstract

The arrangement of n points in a \(\sqrt{n}\times \sqrt{n}\) sized grid offers an efficient and overlap-free way to visualize data. By making use of the Voronoi Relaxation method, we propose a novel post-processing algorithm called VRGrid which allows the arrangement of any two-dimensional data in a grid while minimizing disformation of the input data. This method can be used with popular but overlap-prone projection methods such as t-SNE or MDS to obtain overlap-free and compact visualizations of data. In this chapter, we present how VRGrid works and its complexity, and benchmark it against the state-of-the-art methods Self-Sorting Maps and Distance-preserving Grid using several metrics to measure the quality of the obtained outputs. Given sufficient processing time, VRGrid outperforms these methods in preserving points pairwise-distances and minimizing the disformation of the input data.

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Acknowledgements

We would like to thank the anonymous reviewers for their constructive comments to improve this chapter. This work has been carried out with financial support from the French State, managed by the French National Research Agency (ANR) in the frame of the Involvd project (ANR-20-CE23-0023-04). Experiments presented in this chapter were carried out using the Labo’s in the Sky with Data (LSD), the LaBRI data platform partially funded by Region Nouvelle Aquitaine, and using PlaFRIM experimental testbed, supported by Inria, CNRS (LABRI and IMB), Université de Bordeaux, Bordeaux INP and Conseil Régional d’Aquitaine (see https://www.plafrim.fr/).

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Authors and Affiliations

  1. University of Bordeaux, CNRS, Bordeaux INP, LaBRI, UMR 5800, 33400, Talence, France

    Adrien Halnaut, Romain Giot, Romain Bourqui & David Auber

Authors
  1. Adrien Halnaut
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  2. Romain Giot
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  3. Romain Bourqui
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  4. David Auber
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Corresponding author

Correspondence to Adrien Halnaut .

Editor information

Editors and Affiliations

  1. Dept. of Computer Science, Central Washington University, Ellensburg, WA, USA

    Boris Kovalerchuk

  2. Darmstadt University of Applied Sciences, Darmstadt, Germany

    Kawa Nazemi

  3. Dept. of Computer Science, Central Washington University, Ellensburg, WA, USA

    Răzvan Andonie

  4. ISEL, Polytechnic Institute of Lisbon, Lisboa, Portugal

    Nuno Datia

  5. Department of Informatics, London South Bank University, London, UK

    Ebad Bannissi

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Halnaut, A., Giot, R., Bourqui, R., Auber, D. (2024). Computation of Pixel-Oriented Grid Layout for 2D Datasets Using VRGrid. In: Kovalerchuk, B., Nazemi, K., Andonie, R., Datia, N., Bannissi, E. (eds) Artificial Intelligence and Visualization: Advancing Visual Knowledge Discovery. Studies in Computational Intelligence, vol 1126. Springer, Cham. https://doi.org/10.1007/978-3-031-46549-9_8

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