Urban Image Study can be generalized as an approach of understanding cities based on geo-tagged images using deep learning technology. This talk includes our experience from both academic research and practical projects. Different aspects, such as city color analysis, assessment of urban visual environment, and city sensing score, will be discussed. The platform of CityFace and CityEye will also be introduced as tools we developed for collecting, recognizing, and sharing urban image data.
About the Speaker:
Mr. LIU Liu graduated with a Master in City Planning from the Department of Urban Study and Planning, MIT in 2014. He received his bachelor’s degree from Tongji University in 2012. His research interests include data mining, visualization, and city image study. He worked in MTA, NYC for visualizing & analyzing ACF dataset, and processing data in connection with GTFS dataset. After coming back in China, he worked as a data researcher in the China Academy of Urban Planning and Design, where he participated in a series of planning projects. He was appointed as an academic advisor for Tencent in 2015 in charge of the national human flow research, which is part of the national urban system planning. When he founded the group of Citory in 2016, he put forward the concept of urban image study, and based on which he developed projects like “C-IMAGE”, and “StreeTalk”. His group won the prize of seed in SODA in 2016. He co-founded CitoryTech in 2017. He is currently working as the founder and CEO of CitoryTech and a researcher of Urban Mobility Lab in MIT.
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CENTRE OF URBAN STUDIES AND URBAN PLANNING
THE UNIVERSITY OF HONG KONG