How machine learning and ?computer vision? will transform our cities In 1969, William H. ?Holly? Whyte decided to analyze, and eventually decode, New York City?s rambunctious street life. A famed author, Whyte, along with a handful of collaborators, was recruited by the city?s planning commission to set up cameras and surreptitiously track human activity.

Whyte and his team spent countless afternoons filming parks, plazas, and crosswalks, and even more time counting, crossing out, analyzing, and quantifying footage. Notations were made for how people met and shook hands. Pedestrian movement was mapped on pads of graph paper. To get accurate assessments of activity at a street corner, Whyte?s researchers manually screened people caught waiting for lights to change. Imagine how much time it took to figure out that at the garden of St. Bartholomew?s Church, the average density at lunch time is 12 to 14 people per 1,000 square feet. Observe a city street corner, crosswalk, or plaza long enough, and eventually, energy and entropy give way to understanding. The public greeted Whyte?s work with curiosity and amusement. ?One thing he has discovered is where people schmooze,? deadpanned a 1974 New York Times article. ?The other thing he has discovered is that they like it.?
Whyte?s Street Life Project was a revelation. Whyte offered nuggets not of gold, but of actionable data, which helped shape city policy: peak versus off-peak activity, average densities, walking patterns....