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International Conference on Spatial Information Theory

COSIT 2005: Spatial Information Theory pp 283–299Cite as

On Internal Cardinal Direction Relations

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3693))

Abstract

Internal Cardinal Direction (ICD) relations can be considered as the refinement to the contains/within topological relation. It is widely used to describe the position of an object in a region. In this paper, three ICD models with varying degrees of details are presented – ICD-5, ICD-9 and ICD-13. In each of these, the notion of a “middle part” is defined using Minimum Bounding Rectangles (MBR). Then focusing on ICD-9, three representation methods are discussed. They are major portion, point set of intersections and proportions of intersections respectively. The ICD-9 model is validated by a cognitive experiment, which helped to determine the size of the middle part in ICD-9 and validate the MBR-based partition method. Based on a psychological theory about vague predicates, conceptual neighborhood and intersection of ICD relations are also discussed briefly.

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Author information

Authors and Affiliations

  1. Institute of Remote Sensing and Geographic Information Systems, Peking University, Beijing, 100871, P.R. China

    Yu Liu, Xiaoming Wang, Xin Jin & Lun Wu

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  1. Yu Liu
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  2. Xiaoming Wang
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  3. Xin Jin
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  4. Lun Wu
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Editor information

Editors and Affiliations

  1. School of Computing, University of Leeds, LS2 9JT, Leeds, United Kingdom

    Anthony G. Cohn

  2. Department of Geography, State University of New York at Buffalo, 105 Wilkeson Quad, 14261, Buffalo, NY, USA

    David M. Mark

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Liu, Y., Wang, X., Jin, X., Wu, L. (2005). On Internal Cardinal Direction Relations. In: Cohn, A.G., Mark, D.M. (eds) Spatial Information Theory. COSIT 2005. Lecture Notes in Computer Science, vol 3693. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11556114_18

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  • DOI: https://doi.org/10.1007/11556114_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28964-7

  • Online ISBN: 978-3-540-32020-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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