Space-Time Kernel Density Estimation for Real-Time Interactive Visual Analytics

Date
2017-01-04
Authors
Eaglin, Todd
Cho, Isaac
Ribarsky, William
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Abstract
We present a GPU-based implementation of the Space-Time Kernel Density Estimation (STKDE) that provides massive speed up in analyzing spatial- temporal data. In our work we are able to achieve sub- second performance for data sizes transferable over the Internet in realistic time. We have integrated this into web-based visual interactive analytics tools for analyzing spatial-temporal data. The resulting inte- grated visual analytics (VA) system permits new anal- yses of spatial-temporal data from a variety of sources. Novel, interlinked interface elements permit efficient, meaningful analyses.
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Keywords
Analytics, GPU, Space-Time, Visualization
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