Quantifying the Presence of Graffiti in Urban Environments

Eric K. Tokuda, Roberto M. Cesar, Claudio T. Silva

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Graffiti is a common phenomenon in urban scenarios. Differently from urban art, graffiti tagging is a vandalism act and many local governments are putting great effort to combat it. The graffiti map of a region can be a very useful resource because it may allow one to potentially combat vandalism in locations with high level of graffiti and also to cleanup saturated regions to discourage future acts. There is currently no automatic way of obtaining a graffiti map of a region and it is obtained by manual inspection by the police or by popular participation. In this sense, we describe an ongoing work where we propose an automatic way of obtaining a graffiti map of a neighbourhood. It consists of the systematic collection of street view images followed by the identification of graffiti tags in the collected dataset and finally, in the calculation of the proposed graffiti level of that location. We validate the proposed method by evaluating the geographical distribution of graffiti in a city known to have high concentration of graffiti - São Paulo, Brazil.

Original languageEnglish (US)
Title of host publication2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538677896
DOIs
StatePublished - Apr 1 2019
Event2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Kyoto, Japan
Duration: Feb 27 2019Mar 2 2019

Publication series

Name2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings

Conference

Conference2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019
CountryJapan
CityKyoto
Period2/27/193/2/19

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Keywords

  • computer vision
  • graffiti
  • machine learning
  • street view
  • urban computing

ASJC Scopus subject areas

  • Information Systems and Management
  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems

Cite this

Tokuda, E. K., Cesar, R. M., & Silva, C. T. (2019). Quantifying the Presence of Graffiti in Urban Environments. In 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings [8679113] (2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIGCOMP.2019.8679113