A feasibility study of crowdsourcing and Google street view to determine sidewalk accessibility

We explore the feasibility of using crowd workers from Amazon Mechanical Turk to identify and rank sidewalk accessibility issues from a manually curated database of 100 Google Street View images. We examine the effect of three different interactive labeling interfaces (Point, Rectangle, and Outline)...

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Bibliographic Details
Main Authors:	Kotaro HARA, LE, Victoria, FROEHLICH, Jon
Format:	text
Language:	English
Published:	Institutional Knowledge at Singapore Management University 2012
Subjects:	Software Engineering Urban Studies and Planning
Online Access:	https://ink.library.smu.edu.sg/sis_research/4009 https://ink.library.smu.edu.sg/context/sis_research/article/5011/viewcontent/Hara_AFeasibilityStudyOfCrowdsourcingAndGoogleStreetViewToDetermineSidewalkAccessibility_ASSETS2012PosterPaper.pdf
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Institution:	Singapore Management University
Language:	English

id	sg-smu-ink.sis_research-5011
record_format	dspace
spelling	sg-smu-ink.sis_research-50112019-11-06T05:44:06Z A feasibility study of crowdsourcing and Google street view to determine sidewalk accessibility Kotaro HARA, LE, Victoria FROEHLICH, Jon We explore the feasibility of using crowd workers from Amazon Mechanical Turk to identify and rank sidewalk accessibility issues from a manually curated database of 100 Google Street View images. We examine the effect of three different interactive labeling interfaces (Point, Rectangle, and Outline) on task accuracy and duration. We close the paper by discussing limitations and opportunities for future work. 2012-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/4009 info:doi/10.1145/2384916.2384989 https://ink.library.smu.edu.sg/context/sis_research/article/5011/viewcontent/Hara_AFeasibilityStudyOfCrowdsourcingAndGoogleStreetViewToDetermineSidewalkAccessibility_ASSETS2012PosterPaper.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Software Engineering Urban Studies and Planning
institution	Singapore Management University
building	SMU Libraries
continent	Asia
country	Singapore Singapore
content_provider	SMU Libraries
collection	InK@SMU
language	English
topic	Software Engineering Urban Studies and Planning
spellingShingle	Software Engineering Urban Studies and Planning Kotaro HARA, LE, Victoria FROEHLICH, Jon A feasibility study of crowdsourcing and Google street view to determine sidewalk accessibility
description	We explore the feasibility of using crowd workers from Amazon Mechanical Turk to identify and rank sidewalk accessibility issues from a manually curated database of 100 Google Street View images. We examine the effect of three different interactive labeling interfaces (Point, Rectangle, and Outline) on task accuracy and duration. We close the paper by discussing limitations and opportunities for future work.
format	text
author	Kotaro HARA, LE, Victoria FROEHLICH, Jon
author_facet	Kotaro HARA, LE, Victoria FROEHLICH, Jon
author_sort	Kotaro HARA,
title	A feasibility study of crowdsourcing and Google street view to determine sidewalk accessibility
title_short	A feasibility study of crowdsourcing and Google street view to determine sidewalk accessibility
title_full	A feasibility study of crowdsourcing and Google street view to determine sidewalk accessibility
title_fullStr	A feasibility study of crowdsourcing and Google street view to determine sidewalk accessibility
title_full_unstemmed	A feasibility study of crowdsourcing and Google street view to determine sidewalk accessibility
title_sort	feasibility study of crowdsourcing and google street view to determine sidewalk accessibility
publisher	Institutional Knowledge at Singapore Management University
publishDate	2012
url	https://ink.library.smu.edu.sg/sis_research/4009 https://ink.library.smu.edu.sg/context/sis_research/article/5011/viewcontent/Hara_AFeasibilityStudyOfCrowdsourcingAndGoogleStreetViewToDetermineSidewalkAccessibility_ASSETS2012PosterPaper.pdf
_version_	1770574118406586368

A feasibility study of crowdsourcing and Google street view to determine sidewalk accessibility

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