Modelling of Building Interiors with Mobile Phone Sensor Data

Creating as-built plans of building interiors is a challenging task. In this paper we present a semi-automatic modelling system for creating residential building interior plans and their integration with existing map data to produce building models. Taking a set of imprecise measurements made with a...

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Bibliographic Details
Main Authors: Julian Rosser, Jeremy Morley, Gavin Smith
Format: Article
Language:English
Published: MDPI AG 2015-06-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:http://www.mdpi.com/2220-9964/4/2/989
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spelling doaj-67c1fe40ef064579ac60d68cd413b77c2020-11-24T22:23:15ZengMDPI AGISPRS International Journal of Geo-Information2220-99642015-06-0142989101210.3390/ijgi4020989ijgi4020989Modelling of Building Interiors with Mobile Phone Sensor DataJulian Rosser0Jeremy Morley1Gavin Smith2Nottingham Geospatial Institute, University of Nottingham, Triumph Road, Nottingham NG7 2TU, UKOrdnance Survey, Explorer House, Adanac Drive, Southampton SO16 0AS, UKHorizon Digital Economy Research, University of Nottingham, Triumph Road, Nottingham NG7 2TU, UKCreating as-built plans of building interiors is a challenging task. In this paper we present a semi-automatic modelling system for creating residential building interior plans and their integration with existing map data to produce building models. Taking a set of imprecise measurements made with an interactive mobile phone room mapping application, the system performs spatial adjustments in accordance with soft and hard constraints imposed on the building plan geometry. The approach uses an optimisation model that exploits a high accuracy building outline, such as can be found in topographic map data, and the building topology to improve the quality of interior measurements and generate a standardised output. We test our system on building plans of five residential homes. Our evaluation shows that the approach enables construction of accurate interior plans from imprecise measurements. The experiments report an average accuracy of 0.24 m, close to the 0.20 m recommended by the CityGML LoD4 specification.http://www.mdpi.com/2220-9964/4/2/989buildinggeometrysurveyingmappingmodelling
collection DOAJ
language English
format Article
sources DOAJ
author Julian Rosser
Jeremy Morley
Gavin Smith
spellingShingle Julian Rosser
Jeremy Morley
Gavin Smith
Modelling of Building Interiors with Mobile Phone Sensor Data
ISPRS International Journal of Geo-Information
building
geometry
surveying
mapping
modelling
author_facet Julian Rosser
Jeremy Morley
Gavin Smith
author_sort Julian Rosser
title Modelling of Building Interiors with Mobile Phone Sensor Data
title_short Modelling of Building Interiors with Mobile Phone Sensor Data
title_full Modelling of Building Interiors with Mobile Phone Sensor Data
title_fullStr Modelling of Building Interiors with Mobile Phone Sensor Data
title_full_unstemmed Modelling of Building Interiors with Mobile Phone Sensor Data
title_sort modelling of building interiors with mobile phone sensor data
publisher MDPI AG
series ISPRS International Journal of Geo-Information
issn 2220-9964
publishDate 2015-06-01
description Creating as-built plans of building interiors is a challenging task. In this paper we present a semi-automatic modelling system for creating residential building interior plans and their integration with existing map data to produce building models. Taking a set of imprecise measurements made with an interactive mobile phone room mapping application, the system performs spatial adjustments in accordance with soft and hard constraints imposed on the building plan geometry. The approach uses an optimisation model that exploits a high accuracy building outline, such as can be found in topographic map data, and the building topology to improve the quality of interior measurements and generate a standardised output. We test our system on building plans of five residential homes. Our evaluation shows that the approach enables construction of accurate interior plans from imprecise measurements. The experiments report an average accuracy of 0.24 m, close to the 0.20 m recommended by the CityGML LoD4 specification.
topic building
geometry
surveying
mapping
modelling
url http://www.mdpi.com/2220-9964/4/2/989
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AT jeremymorley modellingofbuildinginteriorswithmobilephonesensordata
AT gavinsmith modellingofbuildinginteriorswithmobilephonesensordata
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