%0 Conference Paper %1 Telea:2010:IEB:2421836.2421847 %A Telea, A. %A Ersoy, O. %B Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization %C Aire-la-Ville, Switzerland, Switzerland %D 2010 %I Eurographics Association %K bundles computergraphics drawing edge graph image-based large visualisation %P 843--852 %R 10.1111/j.1467-8659.2009.01680.x %T Image-based edge bundles: simplified visualization of large graphs %U http://dx.doi.org/10.1111/j.1467-8659.2009.01680.x %X We present a new approach aimed at understanding the structure of connections in edge-bundling layouts. We combine the advantages of edge bundles with a bundle-centric simplified visual representation of a graph's structure. For this, we first compute a hierarchical edge clustering of a given graph layout which groups similar edges together. Next, we render clusters at a user-selected level of detail using a new image-based technique that combines distance-based splatting and shape skeletonization. The overall result displays a given graph as a small set of overlapping shaded edge bundles. Luminance, saturation, hue, and shading encode edge density, edge types, and edge similarity. Finally, we add brushing and a new type of semantic lens to help navigation where local structures overlap. We illustrate the proposed method on several real-world graph datasets.

@inproceedings{Telea:2010:IEB:2421836.2421847, abstract = {We present a new approach aimed at understanding the structure of connections in edge-bundling layouts. We combine the advantages of edge bundles with a bundle-centric simplified visual representation of a graph's structure. For this, we first compute a hierarchical edge clustering of a given graph layout which groups similar edges together. Next, we render clusters at a user-selected level of detail using a new image-based technique that combines distance-based splatting and shape skeletonization. The overall result displays a given graph as a small set of overlapping shaded edge bundles. Luminance, saturation, hue, and shading encode edge density, edge types, and edge similarity. Finally, we add brushing and a new type of semantic lens to help navigation where local structures overlap. We illustrate the proposed method on several real-world graph datasets.}, acmid = {2421847}, added-at = {2013-06-13T10:57:53.000+0200}, address = {Aire-la-Ville, Switzerland, Switzerland}, author = {Telea, A. and Ersoy, O.}, biburl = {https://www.bibsonomy.org/bibtex/203e26e42b1a5d7e777503b47571f3fa3/rwoz}, booktitle = {Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization}, description = {Image-based edge bundles}, doi = {10.1111/j.1467-8659.2009.01680.x}, interhash = {06d953eebeba2be06aa548e8bf311565}, intrahash = {03e26e42b1a5d7e777503b47571f3fa3}, keywords = {bundles computergraphics drawing edge graph image-based large visualisation}, location = {Bordeaux, France}, numpages = {10}, pages = {843--852}, publisher = {Eurographics Association}, series = {EuroVis'10}, timestamp = {2013-06-13T10:57:53.000+0200}, title = {Image-based edge bundles: simplified visualization of large graphs}, url = {http://dx.doi.org/10.1111/j.1467-8659.2009.01680.x}, year = 2010 }