“Detecting Advertising on Building Façades With Computer Vision”, 2019 ():
Outdoor advertising influences the visual environment of any modern city. Advertising and information signs on building façades are one of the types of outdoor advertising. As a rule, there are laws and design codes in cities that define permissible look of such signs.
At the same time, in metropolises, there is a problem of timely detection of advertising constructions on façades that violate these rules. City-scale monitoring of façade conditions is beyond the capabilities of any city’s authorities.
To address this issue, we propose a solution which combines street-view maps and machine learning to automate the process of searching for law-breaking advertising objects on building façades. We develop a dataset for a machine learning model and a set of checks for detected advertising objects to check their legality.
The resulting approach can provide data for future research and help maintain coherent urban visual environment.
[Keywords: urban studies, urban visual environment, computer vision, illegal advertising, building façades, machine learning]