"The Sights & Sounds of 18th Century Paris Get Recreated with 3D Audio and Animation"

From Open Culture:

In what is often called the “Early Modern” period, or the “Long Eighteenth Century,” Europe witnessed an explosion of satire, not only as a political and literary weapon, but as a means of reacting to a whole new way of life that arose in the cities—principally London and Paris—as a displaced rural population and expanding bourgeoisie radically altered the character of urban life. In England, poets like Alexander Pope and Jonathan Swift savaged their rivals in print, while also commenting on the increasing pace and declining tastes of the city.

In France, Voltaire punched up, using his pen to needle Parisian authorities, serving 11 months in the Bastille for a satirical verse accusing the Regent of incest. Despite the hugely successful premiere of his play Oedipus seven months after his release, Voltaire would ultimately be exiled from his beloved city for 28 years, returning in 1778 at the age of 83.

Now, of course, Parisians celebrate Voltaire in every possible way, but what would it have been like to have experienced the city during his lifetime, when it became the buzzing center of European intellectual life? In the video recreation above, we can partially answer that question by experiencing what 18th century Paris may have looked and sounded like, according to musicologist Mylène Pardoen, who designed this “historical audio reconstitution,” writes CNRS News, with a “team of historians, sociologists and specialists in 3D representations.”

The team chose to animate “the Grand Châtelet district, between the Pont au Change and Pont Notre Dame bridges” because, Pardoen explains, the neighborhood “concentrates 80% of the background and sound environments of Paris in that era, whether through familiar trades—shopkeepers, craftsmen, boatmen, washerwomen on the banks of the Seine… or the diversity of acoustic possibilities, like the echo heard under a bridge or in a covered passageway.” The result is “the first 3D reconstruction based solely on a sonic background.”

“We are the whipped cream of Europe,” Voltaire once said of his Paris, a luxurious, aristocratic world....

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Between 1500 and 1900 Paris went from 8th largest city in the world with a population of around 185,000 to 3rd largest in the world with a population of, depending on how far out from the city center you measured, 2.7 to 3.6 million.
Back in the day those big cities were aromatic, see the first link below, if interested.

Related:
"When Paris’s Streets Were Paved With Filth"
Faux Paris
"What Makes Paris Look Like Paris?"

From a source we don't link to often enough, Communications of the Association for Computing Machinery. Thanks to a friend:
Communications of the ACM, December 2015, Vol. 58 No. 12, Pages 103-110
10.1145/2830541

Given a large repository of geo-tagged imagery, we seek to automatically find visual elements, for example windows, balconies, and street signs, that are most distinctive for a certain geo-spatial area, for example the city of Paris. This is a tremendously difficult task as the visual features distinguishing architectural elements of different places can be very subtle. In addition, we face a hard search problem: given all possible patches in all images, which of them are both frequently occurring and geographically informative? To address these issues, we propose to use a discriminative clustering approach able to take into account the weak geographic supervision. We show that geographically representative image elements can be discovered automatically from Google Street View imagery in a discriminative manner. We demonstrate that these elements are visually interpretable and perceptually geo-informative. The discovered visual elements can also support a variety of computational geography tasks, such as mapping architectural correspondences and influences within and across cities, finding representative elements at different geo-spatial scales, and geographically informed image retrieval.

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 Figure 1. These two photos might seem nondescript, but each contains hints about which city it might belong to. Given a large image database of a given city, our algorithm is able to automatically discover the geographically informative elements (patch clusters to the right of each photo) that help in capturing its "look and feel." On the left, the emblematic street sign, a balustrade window, and the balcony support are all very indicative of Paris, while on the right, the neoclassical columned entryway sporting a balcony, a Victorian window, and, of course, the cast-iron railings are very much features of London....

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