Cloud-Based Geospatial 3D Image Spaces—A Powerful Urban Model for the Smart City

In this paper, we introduce the concept and an implementation of geospatial 3D image spaces as new type of native urban models. 3D image spaces are based on collections of georeferenced RGB-D imagery. This imagery is typically acquired using multi-view stereo mobile mapping systems capturing dense s...

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Main Authors: Stephan Nebiker, Stefan Cavegn, Benjamin Loesch
Format: Article
Language:English
Published: MDPI AG 2015-10-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:http://www.mdpi.com/2220-9964/4/4/2267
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spelling doaj-4bc275af7319427d8c9da7aae1308b8a2020-11-24T21:03:15ZengMDPI AGISPRS International Journal of Geo-Information2220-99642015-10-01442267229110.3390/ijgi4042267ijgi4042267Cloud-Based Geospatial 3D Image Spaces—A Powerful Urban Model for the Smart CityStephan Nebiker0Stefan Cavegn1Benjamin Loesch2Institute of Geomatics Engineering, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Gründenstrasse 40, 4132 Muttenz, SwitzerlandInstitute of Geomatics Engineering, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Gründenstrasse 40, 4132 Muttenz, SwitzerlandInstitute of Geomatics Engineering, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Gründenstrasse 40, 4132 Muttenz, SwitzerlandIn this paper, we introduce the concept and an implementation of geospatial 3D image spaces as new type of native urban models. 3D image spaces are based on collections of georeferenced RGB-D imagery. This imagery is typically acquired using multi-view stereo mobile mapping systems capturing dense sequences of street level imagery. Ideally, image depth information is derived using dense image matching. This delivers a very dense depth representation and ensures the spatial and temporal coherence of radiometric and depth data. This results in a high-definition WYSIWYG (“what you see is what you get”) urban model, which is intuitive to interpret and easy to interact with, and which provides powerful augmentation and 3D measuring capabilities. Furthermore, we present a scalable cloud-based framework for generating 3D image spaces of entire cities or states and a client architecture for their web-based exploitation. The model and the framework strongly support the smart city notion of efficiently connecting the urban environment and its processes with experts and citizens alike. In the paper we particularly investigate quality aspects of the urban model, namely the obtainable georeferencing accuracy and the quality of the depth map extraction. We show that our image-based georeferencing approach is capable of improving the original direct georeferencing accuracy by an order of magnitude and that the presented new multi-image matching approach is capable of providing high accuracies along with a significantly improved completeness of the depth maps.http://www.mdpi.com/2220-9964/4/4/2267smart cityurban modelingmobile mappingstereovisionimage matchinggeoreferencingcloud computing3D monoplottingaugmentation
collection DOAJ
language English
format Article
sources DOAJ
author Stephan Nebiker
Stefan Cavegn
Benjamin Loesch
spellingShingle Stephan Nebiker
Stefan Cavegn
Benjamin Loesch
Cloud-Based Geospatial 3D Image Spaces—A Powerful Urban Model for the Smart City
ISPRS International Journal of Geo-Information
smart city
urban modeling
mobile mapping
stereovision
image matching
georeferencing
cloud computing
3D monoplotting
augmentation
author_facet Stephan Nebiker
Stefan Cavegn
Benjamin Loesch
author_sort Stephan Nebiker
title Cloud-Based Geospatial 3D Image Spaces—A Powerful Urban Model for the Smart City
title_short Cloud-Based Geospatial 3D Image Spaces—A Powerful Urban Model for the Smart City
title_full Cloud-Based Geospatial 3D Image Spaces—A Powerful Urban Model for the Smart City
title_fullStr Cloud-Based Geospatial 3D Image Spaces—A Powerful Urban Model for the Smart City
title_full_unstemmed Cloud-Based Geospatial 3D Image Spaces—A Powerful Urban Model for the Smart City
title_sort cloud-based geospatial 3d image spaces—a powerful urban model for the smart city
publisher MDPI AG
series ISPRS International Journal of Geo-Information
issn 2220-9964
publishDate 2015-10-01
description In this paper, we introduce the concept and an implementation of geospatial 3D image spaces as new type of native urban models. 3D image spaces are based on collections of georeferenced RGB-D imagery. This imagery is typically acquired using multi-view stereo mobile mapping systems capturing dense sequences of street level imagery. Ideally, image depth information is derived using dense image matching. This delivers a very dense depth representation and ensures the spatial and temporal coherence of radiometric and depth data. This results in a high-definition WYSIWYG (“what you see is what you get”) urban model, which is intuitive to interpret and easy to interact with, and which provides powerful augmentation and 3D measuring capabilities. Furthermore, we present a scalable cloud-based framework for generating 3D image spaces of entire cities or states and a client architecture for their web-based exploitation. The model and the framework strongly support the smart city notion of efficiently connecting the urban environment and its processes with experts and citizens alike. In the paper we particularly investigate quality aspects of the urban model, namely the obtainable georeferencing accuracy and the quality of the depth map extraction. We show that our image-based georeferencing approach is capable of improving the original direct georeferencing accuracy by an order of magnitude and that the presented new multi-image matching approach is capable of providing high accuracies along with a significantly improved completeness of the depth maps.
topic smart city
urban modeling
mobile mapping
stereovision
image matching
georeferencing
cloud computing
3D monoplotting
augmentation
url http://www.mdpi.com/2220-9964/4/4/2267
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