Recognizing City Identity via Attribute Analysis of Geo-Tagged Images
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.
Cite
Text
Zhou et al. "Recognizing City Identity via Attribute Analysis of Geo-Tagged Images." European Conference on Computer Vision, 2014. doi:10.1007/978-3-319-10578-9_34Markdown
[Zhou et al. "Recognizing City Identity via Attribute Analysis of Geo-Tagged Images." European Conference on Computer Vision, 2014.](https://mlanthology.org/eccv/2014/zhou2014eccv-recognizing/) doi:10.1007/978-3-319-10578-9_34BibTeX
@inproceedings{zhou2014eccv-recognizing,
title = {{Recognizing City Identity via Attribute Analysis of Geo-Tagged Images}},
author = {Zhou, Bolei and Liu, Liu and Oliva, Aude and Torralba, Antonio},
booktitle = {European Conference on Computer Vision},
year = {2014},
pages = {519-534},
doi = {10.1007/978-3-319-10578-9_34},
url = {https://mlanthology.org/eccv/2014/zhou2014eccv-recognizing/}
}