Adaptive Real-Time Grid Generation from 3D Line Scans for fast Visualization and Data Evaluation

This paper presents a method for the real-time generation of grids from 3D line scan data for in-line scan previews and the evaluation of large point clouds derived from different 3D-scanners. By exploiting the underlying measuring principles, we generate regular grids for each scan operation even if the sensor movement is non-linear. These grids are finally used for NURBS patch approximations, which enable the determination of higher order features, e.g. curvature and quality evaluations. Experimental results at the example of different point clouds illustrate the effectiveness of our methods in practice

Cognitive Foundations for Visual Analytics

In this report, we provide an overview of scientific/technical literature on information visualization and VA. Topics discussed include an update and overview of the extensive literature search conducted for this study, the nature and purpose of the field, major research thrusts, and scientific foundations. We review methodologies for evaluating and measuring the impact of VA technologies as well as taxonomies that have been proposed for various purposes to support the VA community. A cognitive science perspective underlies each of these discussions