Fast Statistically Geometric Reasoning About Uncertain Line Segments in 2D- and 3D-Space

This work addresses the two major drawbacks of current statistical uncertain geometric reasoning approaches. In the first part a framework is presented, that allows to represent uncertain line segments in 2D- and 3D-space and perform statistical test with these practically very important types of entities. The second part addresses the issue of performance of geometric reasoning. A data structure is introduced, that allows the efficient processing of large amounts of statistical tests involving geometric entities. The running times of this approach are finally evaluated experimentally.

• Type: Conference
• Year: 2004
• Where: DAGM
• Authors: Christian Beder
• Keywords: DAGM 2004, Geometric Reasoning, Statistical Tests, Uncertain Geometric Reasoning