License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.COSIT.2022.20
URN: urn:nbn:de:0030-drops-169058
URL: https://drops.dagstuhl.de/opus/volltexte/2022/16905/
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Sohn, Samuel S. ; Mavros, Panagiotis ; Kapadia, Mubbasir ; Hölscher, Christoph

A Computational Method for the Classification of Mental Representations of Objects in 3D Space (Short Paper)

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LIPIcs-COSIT-2022-20.pdf (2 MB)


Abstract

The structure mapping task is a simple method to test people’s mental representations of spatial relationships, and has recently been particularly useful in the study of volumetric spatial cognition such as the spatial memory for locations in multilevel buildings. However, there does not exist a standardised method to analyse such data and structure mapping tasks are typically analysed by human raters, based on criteria defined by the researchers. In this article, we introduce a computational method to assess spatial relationships of objects in the vertical and horizontal domains, which are realized through the structure mapping task. Here, we reanalyse participants' digitised structure maps from an earlier study (N=41) using the proposed computational methodology. Our results show that the new method successfully distinguishes between different types of structure map representations, and is sensitive to learning order effects. This method can be useful to advance the study of volumetric spatial cognition.

BibTeX - Entry

@InProceedings{sohn_et_al:LIPIcs.COSIT.2022.20,
  author =	{Sohn, Samuel S. and Mavros, Panagiotis and Kapadia, Mubbasir and H\"{o}lscher, Christoph},
  title =	{{A Computational Method for the Classification of Mental Representations of Objects in 3D Space}},
  booktitle =	{15th International Conference on Spatial Information Theory (COSIT 2022)},
  pages =	{20:1--20:8},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-257-0},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{240},
  editor =	{Ishikawa, Toru and Fabrikant, Sara Irina and Winter, Stephan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2022/16905},
  URN =		{urn:nbn:de:0030-drops-169058},
  doi =		{10.4230/LIPIcs.COSIT.2022.20},
  annote =	{Keywords: mental representations of space, spatial cognition, structure mapping task, 3D space, volumetric space}
}

Keywords: mental representations of space, spatial cognition, structure mapping task, 3D space, volumetric space
Collection: 15th International Conference on Spatial Information Theory (COSIT 2022)
Issue Date: 2022
Date of publication: 22.08.2022


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