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Entree


What Makes a Place Feel Safe? Analyzing Street View Images to Identify Relevant Visual Elements

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Autor(es):
Moreno-Vera, Felipe ; Brandoli, Bruno ; Poco, Jorge
Número total de Autores: 3
Tipo de documento: Artigo Científico
Fonte: 2024 IEEE/WIC INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE AND INTELLIGENT AGENT TECHNOLOGY, WI-IAT; v. N/A, p. 5-pg., 2024-01-01.
Resumo

Over the past four decades, urban perception has become a vital area of research that intersects multiple fields, such as criminology, psychology, and urban planning. This interdisciplinary approach seeks to understand and interpret how people perceive urban environments and how these perceptions shape their behavior. The surge in data collection methods, driven by modern web technologies and services, has enabled researchers to apply techniques from various domains to better quantify and analyze urban perception. In this study, we present the UrbanFormer, a vision transformer-based model, to address the task of urban perception analysis, leveraging the widely-used Place Pulse 2.0 dataset. Our focus is on the safety category, a key issue in urban perception, while employing vision transformer and explainability methods to provide insights into the decision-making process behind perception analysis. (AU)

Processo FAPESP: 21/07012-0 - Inteligência orientada a dados para análise e percepção de crimes urbanos
Beneficiário:Jorge Luis Poco Medina
Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores