Citizen Visual Search Engine: Detection and Curation of Urban Objects

Increasingly, the ubiquity of satellite imagery has made the data analysis and machine learning of large geographical datasets one of the building blocks of visuospatial intelligence. It is the key to discover current (and predict future) cultural, social, financial and political realities. How can we, as designers and researchers, empower citizens to understand and participate in the design of our cities amid this technological shift? As an initial step towards this broader ambition, a series of creative web applications, in the form of visual search engines, has been developed and implemented to data mine large datasets. Using open sourced deep learning and computer vision libraries, these applications facilitate the searching, detecting and curating of urban objects. In turn, the paper proposes and formulates a framework to design truly citizen-centric creative visual search engines - a contribution to citizen science and citizen journalism in spatial terms.


Published in:
Computer-Aided Architectural Design: Hello, Culture, Caad Futures 2019, 1028, 168-182
Presented at:
18th International Conference on Computer-Aided Architectural Design (CAAD Futures) - Hello, Culture, Daejeon, South Korea, June 26-28, 2019
Year:
Jan 01 2019
Publisher:
Cham, SPRINGER INTERNATIONAL PUBLISHING AG
ISSN:
1865-0929
1865-0937
ISBN:
978-981-13-8410-3
978-981-13-8409-7
Keywords:




 Record created 2019-10-29, last modified 2019-10-29


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