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GPU-Accelerated 2D Point Cloud Visualization Using Smooth Splines for Visual Analytics Applications

Kalbe, Thomas and Tekusová, Tatiana and Schreck, Tobias and Zeilfelder, Frank (2008):
GPU-Accelerated 2D Point Cloud Visualization Using Smooth Splines for Visual Analytics Applications.
pp. 111-125, Comenius University, Bratislava, Spring Conference on Computer Graphics SCCG 2008. Conference Proceedings, [Conference or Workshop Item]

Abstract

We develop an efficient point cloud visualization framework. For efficient navigation in the visualization, we introduce a spline-based technique for the smooth approximation of discrete distance field data. Implemented on the GPU, the approximation technique allows for efficient visualizations and smooth zooming in and out of the distance field data. Combined with a template set of predefined, automatically or interactively adjustable transfer functions, the smooth distance field representation allows for an effective visualization of point cloud data at random abstraction levels. Using the presented technique, sets of point clouds can be effectively analyzed for intra- and inter-point cloud distribution characteristics. The effectiveness and usefulness of our approach is demonstrated by application on various point cloud visualization problems.

Item Type: Conference or Workshop Item
Erschienen: 2008
Creators: Kalbe, Thomas and Tekusová, Tatiana and Schreck, Tobias and Zeilfelder, Frank
Title: GPU-Accelerated 2D Point Cloud Visualization Using Smooth Splines for Visual Analytics Applications
Language: English
Abstract:

We develop an efficient point cloud visualization framework. For efficient navigation in the visualization, we introduce a spline-based technique for the smooth approximation of discrete distance field data. Implemented on the GPU, the approximation technique allows for efficient visualizations and smooth zooming in and out of the distance field data. Combined with a template set of predefined, automatically or interactively adjustable transfer functions, the smooth distance field representation allows for an effective visualization of point cloud data at random abstraction levels. Using the presented technique, sets of point clouds can be effectively analyzed for intra- and inter-point cloud distribution characteristics. The effectiveness and usefulness of our approach is demonstrated by application on various point cloud visualization problems.

Publisher: Comenius University, Bratislava
Uncontrolled Keywords: Forschungsgruppe Visual Search and Analysis (VISA), Transfer functions, Splines, Adaptive distance field approximation, Point clouds, Graphics Processing Unit (GPU)
Divisions: UNSPECIFIED
20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Event Title: Spring Conference on Computer Graphics SCCG 2008. Conference Proceedings
Date Deposited: 16 Apr 2018 09:03
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