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Author (up) Sofia Eleni Spatharioti; Sara Wylie; Seth Cooper pdf  isbn
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  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.  
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  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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