FFTEB: Edge Bundling of Huge Graphs by the Fast Fourier Transform

Abstract : Edge bundling techniques provide a visual simplification of cluttered \ graph drawings or trail sets. While many bundling techniques exist, \ only few recent ones can handle large datasets and also allow selective \ bundling based on edge attributes. We present a new technique \ that improves on both above points, in terms of increasing both the \ scalability and computational speed of bundling, while keeping the \ quality of the results on par with state-of-the-art techniques. For \ this, we shift the bundling process from the image space to the spectral \ (frequency) space, thereby increasing computational speed. We \ address scalability by proposing a data streaming process that allows \ bundling of extremely large datasets with limited GPU memory. \ We demonstrate our technique on several real-world datasets \ and by comparing it with state-of-the-art bundling methods.
Document type :
Conference papers
Complete list of metadatas

Cited literature [41 references]  Display  Hide  Download

https://hal-enac.archives-ouvertes.fr/hal-01533755
Contributor : Laurence Porte <>
Submitted on : Tuesday, July 18, 2017 - 10:05:37 AM
Last modification on : Tuesday, January 30, 2018 - 2:06:02 PM
Long-term archiving on : Saturday, January 27, 2018 - 6:11:34 AM

File

main.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01533755, version 1

Collections

Citation

Antoine Lhuillier, Christophe Hurter, Alexandru Telea. FFTEB: Edge Bundling of Huge Graphs by the Fast Fourier Transform. PacificVis 2017, 10th IEEE Pacific Visualization Symposium, Apr 2017, Seoul, South Korea. ⟨hal-01533755⟩

Share

Metrics

Record views

191

Files downloads

394