Qualitative Reasoning about Imprecise Spatial Information

Abstract

This paper investigates the problem of reasoning about imprecise spatial information. As a representation scheme we assume haze-points that are points surrounded by an area, the haze, denoting the imprecision that is associated with them. Haze-points are related by haze and precedence relations. Using these notions we can build higher dimension objects and relations [Top94a]. This paper focuses on reasoning about spatial imprecision which is formalized as a constraint satisfaction problem over networks of constraints expressed in the language of haze-orders. The main contributions of this paper are (a) a set of preprocessing transformations that decrease the ambiguity which is introduced from unconditional transitivity over the haze relation, and (b) a graph-based data structure which is suitable for efficient inferencing of order relations. 1 Introduction It is generally accepted that neither human perception nor measurement instruments are precise in the information they provide. Th..