We are living in an increasingly urbanized world, with more and more people living in densely populated areas. While this population growth brings immense opportunities and potential, it also presents certain challenges. One of these challenges is understanding how humans interact in densely populated areas, or ‘urban neighborhoods’. A recent study by researchers at the University of Cambridge has shed light on this problem, showing how visual analysis can be used to understand the complex relationship between humans and their environment.

The study used a combination of computer vision and machine learning algorithms to analyze the movements of people in a public space. By analyzing the visual data, the researchers were able to identify patterns in how people interact with each other and the environment. This allowed them to create a ‘visual neighborhood’, which is a representation of the physical and social environment of a given area. The researchers believe this could be used to gain a better insight into how humans interact in densely populated areas, and to inform better urban planning.

Read Full Article Here

source: Phys.org