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Author
Sofia Eleni Spatharioti
;
Sara Wylie
;
Seth Cooper
Title
Identifying and Assessing Points of Interest through Crowdsourced Image Analysis
Type
Conference Article
Year
2018
Publication
ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management
Abbreviated Journal
Iscram 2018
Volume
Issue
Pages
1123-1125
Keywords
crowdsourcing, Amazon Mechanical Turk, points of interest
Abstract
During a natural disaster, major damages to critical structures such as bridges or power lines can severely disrupt community functions for long periods of time, making the task of swiftly identifying this type of damage vital for response and recovery. However, survey flight paths are often designed with a main focus of complete and quick coverage of affected areas through aerial photography, which is then assigned to volunteers to aid in damage report and labeling. We designed a crowdsourcing interface that focuses on locating points of interest and assessing damage using images from survey flights. We tested our design using a disaster and a non-disaster application by recruiting volunteers on Amazon Mechanical Turk. We found that the type of structure may cause difficulties for crowd workers in providing accurate assessments and that designing flights to also target structures may provide higher quality imagery for this type of task.
Address
Corporate Author
Thesis
Publisher
Rochester Institute of Technology
Place of Publication
Rochester, NY (USA)
Editor
Kees Boersma; Brian Tomaszeski
Language
English
Summary Language
English
Original Title
Series Editor
Series Title
Abbreviated Series Title
Series Volume
Series Issue
Edition
ISSN
2411-3387
ISBN
978-0-692-12760-5
Medium
Track
Poster
Expedition
Conference
ISCRAM 2018 Conference Proceedings - 15th International Conference on Information Systems for Crisis Response and Management
Notes
Approved
no
Call Number
Serial
2186
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