7037

Visual Data Mining Using the Point Distribution Tensor

Marcel Ritter, Werner Benger, Biagio Cosenza, Keera Pullman, Hans Moritsch, Wolfgang Leimer
Graduate School for Scientific Computing, University of Innsbruck, Innsbruck, Austria
IARIS The First International Workshop on Computer Vision and Computer Graphics (VisGra), 2012

@inproceedings{DistributionTensor2012},

   author={Marcel Ritter and Werner Benger and Biagio Cosenza and Keera Pullman and Hans Moritsch and Wolfgang Leimer},

   ISBN={978-1-61208-184-7},

   year={2012},

   month={Feb-Mar},

   title={Visual Data Mining Using the Point Distribution Tensor},

   journal={IARIS Workshop on Computer Vision and Computer Graphics – VisGra 2012}

}

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We explore a novel algorithm to analyze arbitrary distributions of 3D-points. Using a direct tensor field visualization technique allows to easily identify regions of linear, planar or isotropic structure. This approach is very suitable for visual data mining and exemplified upon geoscience applications. It allows to distinguish, for example, power lines and flat terrains in LIDAR scans. We furthermore present the work on the optimization of the computationally intensive algorithm using OpenCL and potentially utilizing the Insieme optimizing compiler framework.
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