An organic visualization of the dynamics and movements inherent in the iconic Shibuya crossing in Tokyo.
The hustle and bustle happening all day long in Shibuya crossing is unique in the world. During rush hour, it has as many as 2,500 pedestrians crossing every time the signal changes. My project consisted in capturing the dynamics of this place through the lens of a public webcam and visualizing them as a set of almost biological parameters: pulse, flows and lights.
While the flow is directly coming from the motion of the pixels in the video, the pulse is derived from the average speed at which the pixels are moving, and the crosswalk light is captured based on the number of moving pixels at the same time (more pixels implies that people are crossing the street in all directions).
I tried to make this project novel by considering the city as a living being whose health features can be monitored. In a time when many efforts are made towards the planet’s sustainability, rethinking the city as a living being emphasizes the need to preserve its essence and to check upon its health status.
This work was inspired by famous timelapses, such as the Koyaanisqatsi by Geoffrey Reggio and Philip Glass or Tokyo Fisheye Time Lapse by darwinfish105, that managed to capture the dynamics of cities.
Fascinated by these works, I also tried to deviate for their form. Although time lapses are very effective at condensing the multitude of movements happening over a long span of time, I was interested in a more real-time and organic output.
However, this effect could be conveyed more intensely if the app was accompanied by a heartrate monitor sound and if the frame rate was higher. Moreover, the real-time version of the app is not working steadily yet and this would benefit from being fixed in the future.
The media object that I created is an OpenFrameworks application. The following video was recorded from my screen while the app was running. Unfortunately due to the recording my app was running slower and the frame rate gets quite low.