Quantifying the presence of graffiti in urban environments

TL;DR

This paper proposes an automated method to map graffiti in urban areas using street view images, aiding in vandalism prevention and cleanup efforts by analyzing graffiti distribution.

Contribution

It introduces a novel automated approach for creating graffiti maps through image collection, graffiti detection, and level calculation, validated in Sao Paulo.

Findings

Effective identification of graffiti tags in street view images.

Geographical distribution analysis of graffiti in Sao Paulo.

Potential to assist urban vandalism management.

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 -- Sao Paulo, Brazil.