Temporal reasoning based on semi-intervals
Artificial Intelligence
Maintaining knowledge about temporal intervals
Communications of the ACM
Qualitative Spatial Representation and Reasoning: An Overview
Fundamenta Informaticae - Qualitative Spatial Reasoning
A hierarchy of boundary-based shape descriptors
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
A compact shape representation for linear geographical objects: the scope histogram
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
Interpreting motion events of pairs of moving objects
Geoinformatica
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In this paper, a qualitative shape representation is described for the purpose of characterising linear geographical and artificial objects. In particular, we focus on the curve progression telling us how objects spread across the landscape. For instance, sinuosities of rivers provide important information about imperilled locations in the case of flood waters. However, precise geometrical descriptions are overdetermined and frequently difficult or sometimes impossible to obtain. By contrast, we introduce a concept which allows curves to be classified on the basis of a qualitative representation that defines properties of linear objects, which derive from how segments of objects are located relative to other segments, arriving at conclusions such as how twisty a curve is. Especially, the new method can be applied if only coarse information is available and even then if objects are given incompletely.