Abstract
There is great importance in understanding whether people perceive an environment as safe or unsafe. Perceptions are influenced by the built environment, and through better understanding, design interventions can be made to improve the feeling of safety. There is a rich body of research on this topic, yet it requires a lot of manual effort. In this work, we present an approach named Computational Systematic Social Observation (CSSO) to automate the collection and analysis process. The approach uses Google Street View and the Google Vision API to extract characteristics (herein referred to as features) of the built environment that is used to automate the process of understanding whether people will feel fear or safety. In testing this approach, we extracted
Original language | English |
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Article number | 45 |
Journal | Crime Science |
Volume | 13 |
DOIs | |
Publication status | Published - 19 Dec 2024 |