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Sketch maps and verbal descriptions in structuring space

Sketch maps and verbal descriptions in structuring space

Wang, Jia ORCID: 0000-0003-4379-9724 and Li, Rui (2018) Sketch maps and verbal descriptions in structuring space. In: AGILE 21st Conference on Geo-information Science, 12 June - 15 June 2018, Lund, Sweden. (In Press)

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Abstract

This paper reports the preliminary results of a study that aims at designing an intelligent navigation system providing automated scene descriptions and effective directions for a wayfinder. In general, there are two ways for humans to communicate about a route and its surroundings, which are verbal descriptions and graphic depictions (for instance sketch maps). Spatial preposition in language and spatial arrangement of depicted objects reflect how humans select and localise spatial objects relating to a route in navigation. This information is critical to the development of an effective cognitive model for an intelligent navigation system. An experiment including two different sizes of environments was carried out. Participants were asked to provide route instructions using both sketch maps and verbal directions. The comparisons of the two types of route instructions focus on spatial disposition and are based on the linguistic conceptual framework proposed by Talmy. The results demonstrate the basic distinctions of geometry and spatial relation in structuring a walking space.

Item Type: Conference or Conference Paper (Speech)
Uncontrolled Keywords: sketch map, verbal description, navigation, language, Ground, Figure
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Department of Computing & Information Systems
Faculty of Architecture, Computing & Humanities > Greenwich GI Science Research Group
Last Modified: 18 Dec 2018 15:28
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/19725

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