Paper Info
Title
Haiti earthquake photo tagging: Lessons on crowdsourcing in-depth image classifications
Abstract
Facilitated by the latest advances of information technologies, online human computing resources provide researchers unprecedented opportunities to resolve a class of real-world problems that are challenging even to the computer algorithms, and yet manageable to human intelligence if working units are well organized. A problem in this category is image labeling, recognizing and categorizing targets in the images. In this paper, we describe an online platform that leverages human computation resources to resolve an image labeling task - classifying damage patterns in post-disaster photos. The underlying information valuable to us is not only the existence of damage in the image, but also its patterns and severity. We hope this study can provide new perspectives to enhance the design of crowdsourcing projects in future.
Year
DOI
Venue
2012
10.1109/ICDIM.2012.6360130
ICDIM
Keywords
Field
DocType
computer algorithm,image labeling task,image target recognition,crowdsourcing project,human computation resource,information technology,disasters,post-disaster photo,resource allocation,earthquakes,in-depth image classifications,haiti earthquake photo tagging,image classification,damage severity,image retrieval,internet,damage pattern classification,structural damage information retrieval,image target categorization,human intelligence,groupware,web platform,online human computing resource,accuracy,civil engineering
Data science,Data mining,Information retrieval,Human intelligence,Computer science,Collaborative software,Crowdsourcing,Information technology,Image retrieval,Resource allocation,Contextual image classification,The Internet
Conference
ISSN
ISBN
Citations 
pending
978-1-4673-2428-1
2
PageRank 
References 
Authors
0.36
6
4
Name
Order
Citations
PageRank
Zhi Zhai1275.01
Tracy Kijewski-Correa271.63
David Hachen39612.38
Gregory R. Madey444149.83