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Identifying Divergent Building Structures Using Fuzzy Clustering of Isovist Features

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Progress in Location-Based Services 2016

Part of the book series: Lecture Notes in Geoinformation and Cartography ((ICA))

Abstract

Nowadays indoor navigation and the understanding of indoor maps and floor plans are becoming increasingly important fields of research and application. This paper introduces clustering of floor plan areas of buildings according to different characteristics. These characteristics consist of computed human perception of space, namely isovist features. Based on the calculated isovist features of floorplans we can show the possible existence of greatly varying alternative routes inside and around buildings. These routes are archetypes, since they are products of archetypal analysis, a fuzzy clustering method that allows the identification of observations with extreme values. Besides archetypal routes in a building we derive floor plan area archetypes. This has the intention of gaining more knowledge on how parts of selected indoor environments are perceived by humans. Finally, our approach helps to find a connection between subjective human perceptions and defined functional spaces in indoor environments.

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Author information

Authors and Affiliations

  1. Mobile and Distributed Systems Group, LMU Munich, Munich, Germany

    Sebastian Feld

  2. Department of Cartography, Technische Universität München, Munich, Germany

    Hao Lyu

  3. Applied Geoinformatics, University of Augsburg, Augsburg, Germany

    Andreas Keler

Authors
  1. Sebastian Feld
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  2. Hao Lyu
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  3. Andreas Keler
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Corresponding author

Correspondence to Sebastian Feld .

Editor information

Editors and Affiliations

  1. Research Group Cartography, Vienna University of Technology , Vienna, Wien, Austria

    Georg Gartner

  2. Department of Geography, University of Zurich , Zurich, Zürich, Switzerland

    Haosheng Huang

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Feld, S., Lyu, H., Keler, A. (2017). Identifying Divergent Building Structures Using Fuzzy Clustering of Isovist Features. In: Gartner, G., Huang, H. (eds) Progress in Location-Based Services 2016. Lecture Notes in Geoinformation and Cartography(). Springer, Cham. https://doi.org/10.1007/978-3-319-47289-8_8

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