Profile

Ali Can Demiralp, M. Sc.
Room K111
Phone: +49 241 80 29732
Fax: +49 241 80 22134
Email: demiralp@vr.rwth-aachen.de


Publications


Daniel Zielasko, Xiaoqing Zhao, Ali Can Demiralp, Torsten Wolfgang Kuhlen, Benjamin Weyers
Computers & Graphics

Relational data with a spatial embedding and depicted as node-link diagram is very common, e.g., in neuroscience, and edge bundling is one way to increase its readability or reveal hidden structures. This article presents a 3D extension to kernel density estimation-based edge bundling that is meant to be used in an interactive immersive analysis setting. This extension adds awareness of the edges’ direction when using kernel smoothing and thus implicitly supports both directed and undirected graphs. The method generates explicit bundles of edges, which can be analyzed and visualized individually and as sufficient as possible for a given application context, while it scales linearly with the input size.

» Show BibTeX

@article{ZIELASKO2019,
title = "Voxel-based edge bundling through direction-aware kernel smoothing",
journal = "Computers & Graphics",
volume = "83",
pages = "87 - 96",
year = "2019",
issn = "0097-8493",
doi = "https://doi.org/10.1016/j.cag.2019.06.008",
url = "http://www.sciencedirect.com/science/article/pii/S0097849319301025",
author = "Daniel Zielasko and Xiaoqing Zhao and Ali Can Demiralp and Torsten W. Kuhlen and Benjamin Weyers"}






Claudia Hänel, Ali Can Demiralp, Markus Axer, David Gräßel, Bernd Hentschel, Torsten Wolfgang Kuhlen
19th EG/VGTC Conference on Visualization (EuroVis 2017)

3D-Polarized Light Imaging (3D-PLI) provides data that enables an exploration of brain fibers at very high resolution. However, the visualization poses several challenges. Beside the huge data set sizes, users have to visually perceive the pure amount of information which might be, among other aspects, inhibited for inner structures because of occlusion by outer layers of the brain. We propose a clustering of fiber directions by means of spherical harmonics using a level-of-detail structure by which the user can interactively choose a clustering degree according to the zoom level or details required. Furthermore, the clustering method can be used for the automatic grouping of similar spherical harmonics automatically into one representative. An optional overlay with a direct vector visualization of the 3D-PLI data provides a better anatomical context.



Honorable Mention for Best Short Paper!

» Show BibTeX

@inproceedings {Haenel2017Interactive,
booktitle = {EuroVis 2017 - Short Papers},
editor = {Barbora Kozlikova and Tobias Schreck and Thomas Wischgoll},
title = {{Interactive Level-of-Detail Visualization of 3D-Polarized Light Imaging Data Using Spherical Harmonics}},
author = {H\”anel, Claudia and Demiralp, Ali C. and Axer, Markus and Gr\”assel, David and Hentschel, Bernd and Kuhlen, Torsten W.},
year = {2017},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-043-7},
DOI = {10.2312/eurovisshort.20171145}
}





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