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

Christian Beder
2004 Lecture Notes in Computer Science  
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
more » ... eometric entities. The running times of this approach are finally evaluated experimentally.
doi:10.1007/978-3-540-28649-3_46 fatcat:z4nvugzj2bgc7eklvgdifb5kam