Ordering: A Reliable Qualitative Information for the Alignment of Sketch and Metric Maps

Sahib Jan, Angela Schwering, Jia Wang and Malumbo Chipofya
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Sahib Jan: Institute for Geoinformatics, University of Muenster, Muenster, Germany
Angela Schwering: Institute for Geoinformatics, University of Muenster, Muenster, Germany
Jia Wang: Institute for Geoinformatics, University of Muenster, Muenster, Germany
Malumbo Chipofya: Institute for Geoinformatics, University of Muenster, Muenster, Germany

International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 2014, vol. 8, issue 1, 67-78

Abstract: Sketch maps are externalizations of cognitive maps which are typically distorted, schematized, incomplete, and generalized. Processing spatial information from sketch maps automatically requires reliable formalizations which are not subject to schematization, distortion or other cognitive effects in sketch maps. Based on previous empirical work, the authors identified different sketch aspects such as ordering, topology and orientation to align and integrate spatial information from sketch maps with metric maps qualitatively. This research addresses the question how these qualitative sketch aspects can be formalized for a computational approach for sketch map alignment. In this study, the authors focus on the ordering aspect: ordering of landmarks and street segments along routes and around junctions. The authors first investigate different qualitative representations and propose suitable representations to formalize these aspects. The proposed representations capture qualitative relations between spatial objects in the form of qualitative constraint networks. The authors then evaluate the proposed representations by testing the accuracy of qualitative constraints between sketched objects and their corresponding objects in a metric map. The results of the evaluation show that the proposed representations are suitable for the alignment of spatial objects from sketch maps with metric maps.

Date: 2014
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