@inproceedings{71313bed4b1b494792b43d745ace39e9,
title = "UrbanMM'21: 1st International Workshop on Multimedia Computing for Urban Data",
abstract = "Understanding complex processes that give cities their form traditionally relied primarily on the analysis of various open data statistics in relation to e.g. neighbourhood demographics, economy and mobility. However, recent years have seen an unprecedented increase in the availability and use of city-related sensors, participatory data and social multimedia. As the valuable information about urban challenges is usually encoded across multiple modalities, such as visual (e.g. panoramic, satellite and user-contributed images), text (e.g. social media and participatory data) and open data statistics, extracting this information requires effective multimedia analysis tools. This Workshop will showcase the power of multimedia computing in addressing various urban challenges, ranging from event detection and analysis, location recommendation and crowdedness estimation to more efficient handling of citizen reports and modelling and improving city liveability. In addition, it will serve as an impulse for the multimedia community to intensify research on these interesting, challenging and truly multimodal problems.",
keywords = "city liveability, multimedia computing, urban multimedia data",
author = "Stevan Rudinac and Alessandro Bozzon and Chua, {Tat Seng} and Suzanne Little and Daniel Gatica-Perez and Kiyoharu Aizawa",
year = "2021",
doi = "10.1145/3474085.3478577",
language = "English",
series = "MM 2021 - Proceedings of the 29th ACM International Conference on Multimedia",
publisher = "Association for Computing Machinery (ACM)",
pages = "5696--5697",
editor = "Shen, {Heng Tao} and Zhuang, {Yueting }",
booktitle = "MM 2021 - Proceedings of the 29th ACM International Conference on Multimedia",
address = "United States",
note = "29th ACM International Conference on Multimedia, MM 2021 ; Conference date: 20-10-2021 Through 24-10-2021",
}