

From the overview of the “What Makes Paris Look like Paris?” study:

Consider the two photographs [above], both downloaded from Google Street View. One comes from Paris, the other one from London. Can you tell which is which? Surprisingly, even for these nondescript street scenes, people who have been to Europe tend to do quite well on this task.

In an informal survey, we presented 11 subjects with 100 random Street View images of which 50% were from Paris, and the rest from eleven other cities. We instructed the subjects (who have all been to Paris) to try and ignore any text in the photos, and collected their binary forced-choice responses (Paris / Not Paris).

On average, subjects were correct 79% of the time (std = 6.3), with chance at 50% (when allowed to scrutinize the text, performance for some subjects went up as high as 90%). What this suggests is that people are remarkably sensitive to the geographically-informative features within the visual environment. But what are those features?

In informal debriefings, our subjects suggested that for most images, a few localized, distinctive elements “immediately gave it away”. E.g. for Paris, things like windows with railings, the particular style of balconies, the distinctive doorways, the traditional blue/green/white street signs, etc. were particularly helpful.

Having developed an algorithm to identify the key geo-informative features for a paricular place from a large database of random Street View photographs, the researchers extracted the key elements for a number of cities, including San Francisco:





Apparently it’s bay windows, cheap aluminum windows, poured steps, paneled garage doors and SUVs that makes San Francisco look like San Francisco.

∙ What Makes Paris Look Like Paris? [cmu.edu]

∙ The Paris/Not Paris Test [cmu.edu]