Crowdsourced Database of Street-Level Imagery

Picture of Mapillary crowdsourced database Acquired by Facebook

Mapillary Crowdsourced Database Acquired by Facebook

Mapillary, the Swedish startup that wants to take on Google and others in mapping the world via a crowdsourced database of street-level imagery, has been acquired by Facebook, according to the company’s blog. Terms of the deal aren’t being disclosed.

From an article in Tech Crunch by Steve O’Hear.

The Mapillary team and project will become part of Facebook’s broader open mapping efforts. Mapillary also says its “commitment to OpenStreetMap stays.”

Writes Mapillary co-founder and CEO Jan Erik Solem (who also previously founded Polar Rose, a face recognition solution for mobile and web that Apple bought in 2010):

“From day one of Mapillary, we have been committed to building a global crowdsourced database, street-level imagery platform that allows everyone to get the imagery and data they need to make better maps. With tens of thousands of contributors to our platform and with maps being improved with Mapillary data every single day, we’re now taking the next big step on that journey.”

As Solem notes, Facebook is known to be “building tools and technology to improve maps through a combination of machine learning, satellite imagery and partnerships with mapping communities.” Mapping has immediate use-cases for the social networking behemoth, such as Facebook Marketplaces and its local business offerings, while another application is augmented reality.

This saw it recently acquire another European startup, Scape, news that TechCrunch broke in February. Founded in 2017, Scape Technologies was developing a “Visual Positioning Service” based on computer vision, which lets developers build apps that require location accuracy far beyond the capabilities of GPS alone. The technology initially targeted augmented reality apps, but also had the potential to be used to power applications in mobility, logistics and robotics. More broadly, Scape wanted to enable any machine equipped with a camera to understand its surroundings.

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