• News

    :: 2015 CGLab got funding for a TUBITAK research grant on Data Analytics

    :: 2012 CGLab got funding for a bilateral research grant on Augmented Reality together with UniversitĂ  di Bologna.

    :: 2011 CGLab got funding for two Turk Telekom research grants on Augmented Reality.

    :: 2010 Research results will be presented at ISCIS (UK) Conference.

    :: 2010 CGLab got funding for a TUBITAK research grant on Information Visualization

    :: 2010 CGLab member Selcuk Sumengen got TUBITAK fellowship to collaborate with UC Merced.

    :: 2009 Research results will be presented at CGI (Canada), CASA (NL), HCI (USA) and GeoVis (D) Conferences.

    :: 2008 research results were presented at SIGGRAPH, Information Visualization VRCAI, Cyberworlds and CAA 2008 Conferences.

    :: Istanbul Archaeology Museum Marmaray-Metro Rescue Excavations Symposium (in Turkish)

    :: CGLab members received IBM Faculty Award

    :: CGI 2008 will be in Istanbul and co-organized by CG Lab

    :: Three CS 450 'Computing and Art' course projects will be presented at SIGGRAPH'07 and IEEE InfoVis'07 as poster presentations

    :: CG Lab got awarded with a collaboration project on Medical VR and AR with University of Lecce, Italy

    :: A toolkit for cultural heritage researchers,CH-Tools is freely available

    :: Recent papers will be presented at CGI 2007, HCI 2007, Grapp 2007 and CAA 2007

    :: CG Lab got awarded with Sabanci University internal grant for a transdiciplinary project 'Novel Representation and interaction techniques of complex datasets'

    :: CG Lab participated to the exhibition of Techne digital performance platform between 17-22 April, 2006.

    :: CG Lab got funding for three TUBITAK research projects

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Entropy Guided Visualization And Analysis Of Multivariate Spatio-Temporal Data Generated By Physically Based Simulation

Selcuk Sumengen, Ekrem Serin, Selim Balcisoy. IEEE SciVis 2014, Poster Presentation

Flow fields produced by physically based simulations are subsets of multivariate spatio-temporal data, and have been in interest of many researchers for visualization, since the data complexity makes it difficult to extract representative views for the interpretation of fluid behaviour. We utilize Information Theory to find entropy maps for vector flow fields, and use entropy maps to aid visualization and analysis of the flow fields. Our major contribution is to use Principal Component Analyses (PCA) to find a projection that has the maximal directional variation in polar coordinates for each sampling window in order to generate histograms according to the projected 3D vector field, producing results with fewer artefacts than the traditional methods.

Entropy guided visualization of different data sets are presented to evaluate proposed method for the generation of entropy maps. High entropy regions and coherent directional components of the flow fields are visible without cluttering to reveal fluid behavior in rendered images. In addition to using data sets those are available for research purposes, we have developed a fluid simulation framework using Smoothed Particle Hydrodynamics (SPH) to produce flow fields. SPH is a widely used method for fluid simulations, and used to generate data sets that are difficult to interpret with direct visualization techniques.

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