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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 involvingdoi:10.1007/978-3-540-28649-3_46 fatcat:z4nvugzj2bgc7eklvgdifb5kam