Mug Shots: Bots Scour Google Maps to Find Faces in the Land
- 6:29 am |
We humans tend to see faces where they don’t actually exist. Clouds, the moon, grilled cheese; it’s all a canvas for our imaginations. The psychological tendency to see meaningful images in vague visuals actually has a name—pareidolia—and it’s the basis for a mesmerizing new project.
Berlin-based design studio Onformative created Google Faces, an algorithm-based system that searches Google Maps’ satellite images for landscapes that resemble the human face. The design team, made of up Cedric Kiefer and Julia Laub, stumbled on the idea after previous facial recognition projects kept generating false positives (detecting facial images where there are none).
“We asked ourselves, could a machine using an algorithm find the same faces in nature that a human would recognize?” Kiefer says. “We wanted to explore if this psychological phenomenon could be replicated in a machine.”
To find out, the team created a two part system consisting of one computer running Google Maps and the other running a bot programmed with a facial recognition algorithm that simulates pareidolia. Functioning like a human Google Maps user, the facetracking bot autonomously clicks its way around the world, stopping to gather data whenever it comes across a landscape that resembles a face.
Kiefer notes the computer most often tags locations when it spots dark images in a light environment. For example, a forest with trees casting shadows.
“If you have two or three dark spots, it will always see that as two eyes and the shadow underneath your nose or mouth,” he explains. “That’s often enough for the algorithm to recognize a face.”
The human facial recognition system is a little more discerning and complex. We’re able to recognize profile views, the outline of hair and the contour of chins in simple landscapes, but an image with too much noise (cities, dense forests and topographically complex landscapes) often doesn’t register with us.
The bot has already latitudinally circled the world a few times, but the goal is for it to traverse the entire planet at every Google Map zoom level (there are 17) in order to get the most comprehensive data set. And at a speed of one snapshot analyzed per second, a round-the-world trip can be quite a trek depending on how zoomed in the bot is. Kiefer estimates they’ve only covered 5 percent of the world, which means there are a lot more faces to come.
“We have a long way to go,” he says. “There are probably a lot of faces out there that we just haven’t found yet.”
All images: Courtesy of Google Maps