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Recognizing City Identity via Attribute Analysis of Geo-tagged Images
Bolei Zhou, Liu Liu2, Aude Oliva1, and Antonio Torralba1
1Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
bolei@mit.edu
oliva@mit.edu
torralba@mit.edu
2Department of Urban Studies and Planning, Massachusetts Institute of Technology, Cambridge, MA, USA
lyons66@mit.edu
Abstract. After hundreds of years of human settlement, each city has formed a distinct identity, distinguishing itself from other cities. In this work, we propose to characterize the identity of a city via an attribute analysis of 2 million geo-tagged images from 21 cities over 3 continents. First, we estimate the scene attributes of these images and use this representation to build a higher-level set of 7 city attributes, tailored to the form and function of cities. Then, we conduct the city identity recognition experiments on the geo-tagged images and identify images with salient city identity on each city attribute. Based on the misclassification rate of the city identity recognition, we analyze the visual similarity among different cities. Finally, we discuss the potential application of computer vision to urban planning.
Keywords: Geo-tagged image analysis, attribute, spatial analysis, city identity, urban planning
LNCS 8691, p. 519 ff.
lncs@springer.com
© Springer International Publishing Switzerland 2014