Title
Quantifying Urban Safety Perception on Street View Images
Date Issued
14 December 2021
Access level
metadata only access
Resource Type
conference paper
Author(s)
Publisher(s)
Association for Computing Machinery
Abstract
In the last 40 years, Urban perception has become an important research area covering several fields, such as criminology, psychology, urban planning, Broken windows theory. It aims to analyze and interpret the behavior of the perception in cities. Urban perception focuses on understanding urban environments based on the characteristics of the city. With the rapidly increasing data availability and highly scalable data collection methods powered by modern web services, new techniques from other domains enabled the exploration of solutions to estimate urban perception (i.e., quantify urban perception autonomously). This work presents a methodology to explore the urban perception analysis task. The work relies on the benchmark dataset, Place Pulse. This dataset is used to perform our classification tasks concerning the category of safety in urban perception problems.
Start page
611
End page
616
Language
English
OCDE Knowledge area
Ciencias de la computación
Subjects
Scopus EID
2-s2.0-85128675485
Resource of which it is part
ACM International Conference Proceeding Series
ISBN of the container
978-145039115-3
Conference
ACM International Conference Proceeding Series
Source funding
Sponsor(s)
This work was supported by grant 234-2015-FONDECYT (Master Program) from CienciActiva of the National Council for Science, Technology and Technological Innovation (CONCYTEC-PERU), grant #312483/2018-0 from The Brazilian National Council for Scientific and Technological Development (CNPq-BRAZIL), and Getulio Vargas Foundation.
Sources of information:
Directorio de Producción Científica
Scopus