THE 3rd VISION – 第三只眼 A-Stra Advisors, Atoms Atelier, Currant.ai (Waishan Qiu 邱外山, Xun Liu 刘浔, Xiaokai Huang 黄笑恺, Xu Zhang 张旭, Ruijun Liu 刘瑞珺, Kaining Peng 彭凯宁, Xiaojiang Li 李小江, Junjiao Gan 甘骏焦) Measuring the street environment mostly focused on gross quantities of the environment’s physical features, without figures describing people’s overall perception. Therefore, it is extremely difficult to study the human perception of the street environment. In this case, design and planning is a subjective top-down process and only can be participated and evaluated by experts and architects. Prior research suggests that the enclosure, the human scale, the diversity of a street is directly related to a person’s appreciation of that place (Ewing & Clemente, 2013). With the advance of the autonomous vehicle industry, nowadays computer vision and artificial intelligence have been widely applied to monitor road conditions. Using Google street images, it becomes possible for us to access human overall perception of the built environment. This study takes Shenzhen as an example and applies those state-of-the-art technologies to identify street space quality. Big data becomes an efficient audit tool of the street environment. In other words, it becomes the eyes we used to observe the city. It helps us to investigate the mechanism of the city according to the public’s image of the city and reveals the relationship between human mental experience and the physical environment.
During the exhibition, watching the projection screen with AR & VR devices, visitors can experience how the machine sees the street images. With Google Street images and data collected from an online survey, the correlation between human perception and certain elements (enclosure, human scale and so on in Ewing’s theories, for example) of the street can be testified. When the measurement applied in Shenzhen city, people can identify which street is the most walking-friendly street, showing the relationship between physical activity and urban environment. The measurement process is also implemented in 6 global cities. From the result we can study the attractive factor which contributes to the high-quality street environment.
Credits: Waishan Qiu 邱外山, Xun Liu 刘浔, Xiaokai Huang 黄笑恺, Xu Zhang 张旭, Ruijun Liu 刘瑞珺, Kaining Peng 彭凯宁, Xiaojiang Li 李小江, Junjiao Gan 甘骏焦.
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