Urban Perception: Can We Understand Why a Street Is Safe?

Moreno-Vera F.; Lavi B.; Poco J. · Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2021) · DOI: 10.1007/978-3-030-89817-5_21

Resumen

The importance of urban perception computing is relatively growing in machine learning, particularly in related areas to Urban Planning and Urban Computing. This field of study focuses on developing systems to analyze and map discriminant characteristics that might directly impact the city’s perception. In other words, it seeks to identify and extract discriminant components to define the behavior of a city’s perception. This work will perform a street-level analysis to understand safety perception based on the “visual components”. As our result, we present our experimental evaluation regarding the influence and impact of those visual components on the safety criteria and further discuss how to properly choose confidence on safe or unsafe measures concerning the perceptional scores on the city street levels analysis.

Instituciones: Universidad Católica San Pablo