SOTAVerified

Predicting city safety perception based on visual image content

2019-02-19arXiv 2019Code Available0· sign in to hype

Sergio Acosta, Jorge E. Camargo

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

Safety perception measurement has been a subject of interest in many cities of the world. This is due to its social relevance, and to its effect on some local economic activities. Even though people safety perception is a subjective topic, sometimes it is possible to find out common patterns given a restricted geographical and sociocultural context. This paper presents an approach that makes use of image processing and machine learning techniques to detect with high accuracy urban environment patterns that could affect citizen's safety perception.

Tasks

Benchmark Results

DatasetModelMetricClaimedVerifiedStatus
Google Street ImagesCNNAccuracy81Unverified

Reproductions