For social scientists, developing an empirical connection between the physical appearance of a city and the behavior and health of its inhabitants has proved challenging due to a lack of data on urban appearance. Can we use computers to quantify urban appearance from street-level imagery? We describe Streetscore: a computer vision algorithm that measures the perceived safety of streetscapes. Using Streetscore to evaluate 19 American cities, we find that the average perceived safety has a strong positive correlation with population density and household income; and the variation in perceived safety has a strong positive correlation with income inequality
City streets are the most widely distributed and heavily trafficked urban public spaces. As cities s...
Fig. 1: The violent crime rate in San Francisco is an example of a non-visual city attribute that is...
Kevin Lynch’s The Image of the City (1960) is a seminal urban design theory notable for its clear de...
Which neighborhoods experience physical improvements? In this paper, we introduce a computer vision ...
Social science literature has shown a strong connection between the visual appearance of a city’s ne...
A traveler visiting Rio, Manila or Caracas does not need a report to learn that these cities are une...
A traveler visiting Rio, Manila or Caracas does not need a report to learn that these cities are une...
Given the present size of modern cities, it is beyond the perceptual capacity of most people to deve...
Abstract. Human observers make a variety of perceptual inferences about pictures of places based on ...
Recently, many new studies applying computer vision (CV) to street view imagery (SVI) datasets to ob...
The proliferation of street view images (SVIs) and the constant advancements in deep learning techni...
Urbanization and inequalities are two of the major policy themes of our time, intersecting in large ...
The assessments on human perception of urban spaces are essential for the management and upkeep of s...
Machine learning methods have achieved human-level accuracies in many computer vision and natural la...
The interactions of individuals with city neighbourhoods is determined, in part, by the perceived qu...
City streets are the most widely distributed and heavily trafficked urban public spaces. As cities s...
Fig. 1: The violent crime rate in San Francisco is an example of a non-visual city attribute that is...
Kevin Lynch’s The Image of the City (1960) is a seminal urban design theory notable for its clear de...
Which neighborhoods experience physical improvements? In this paper, we introduce a computer vision ...
Social science literature has shown a strong connection between the visual appearance of a city’s ne...
A traveler visiting Rio, Manila or Caracas does not need a report to learn that these cities are une...
A traveler visiting Rio, Manila or Caracas does not need a report to learn that these cities are une...
Given the present size of modern cities, it is beyond the perceptual capacity of most people to deve...
Abstract. Human observers make a variety of perceptual inferences about pictures of places based on ...
Recently, many new studies applying computer vision (CV) to street view imagery (SVI) datasets to ob...
The proliferation of street view images (SVIs) and the constant advancements in deep learning techni...
Urbanization and inequalities are two of the major policy themes of our time, intersecting in large ...
The assessments on human perception of urban spaces are essential for the management and upkeep of s...
Machine learning methods have achieved human-level accuracies in many computer vision and natural la...
The interactions of individuals with city neighbourhoods is determined, in part, by the perceived qu...
City streets are the most widely distributed and heavily trafficked urban public spaces. As cities s...
Fig. 1: The violent crime rate in San Francisco is an example of a non-visual city attribute that is...
Kevin Lynch’s The Image of the City (1960) is a seminal urban design theory notable for its clear de...