Researchers at Stanford University have developed algorithms that can determine where a neighborhood's political allegiances lie by analyzing the cars on its streets derived from publicly available Google Street View images.
The algorithms trained themselves to identify the make, model, and year of every car produced since 1990 in more than 50 million Google Street View images from 200 U.S. cities. They then compared this information against the American Community Survey demographic database and against presidential election voting data to calculate demographic factors.
The algorithm sorted the cars in all of the images into 2,657 categories by make, model, and year in only 14 days, whereas it would take 15 years for a human working at a rate of six images a minute to complete the job.
Stanford professor Fei-Fei Li says this research "opens up more possibilities of virtually continuous study of our society using sometimes cheaply available visual data."
From Stanford News
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