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Facial recognition technology is booming both for commercial and security purposes, from Amazon scanning faces in its grocery store to police using the software on 117 million Americans.

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But a Berlin-based artist has found a way to confuse these computer vision algorithms with a concept that borrows from the camouflage techniques used by animals.

With the HyperFace project, Adam Harvey uses thousands of "algorithm-specific optimized false faces which reduce the confidence score of your true face," as he told Mashablevia e-mail.

Prototype of the patterns.Credit: HyperFace Prototype by Adam Harvey / ahprojects.com

In other words, these patterns, which can be printed on clothing or textiles, appear to have all facial features that the visual software can interpret as a face, thus overloading and over saturating the algorithm so that it can't really tell which faces are real.

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"In other words, if a computer vision algorithm is expecting a face, give it what it wants," the project's page says.

"I got inspiration from false coloration in the animal kingdom," Harvey said. "HyperFace is about reimagining the figure-ground relationship of the human body to our environment in the context of computer vision."

The technical concept is an extension of Harvey's earlier project, CV Dazzle, in which he used avant-garde hairstyling and makeup designs to break the continuity of a face -- a so-called "anti-face" -- and prevent facial-recognition software from detecting it.

CV Dazzle hair styling.Credit: Adam Harvey

"I think this project could change fashion designers' and architects' approach to modulating the way bodies appear or disappear into the background of a computer vision readable world," Harvey said.

Announced at the Chaos Communications Congress hacking conference in Hamburg, the project was created for Hyphen Labs NeuroSpeculative AfroFeminismand will be presented at Sundance Film Festival on Jan. 16.

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TopicsFacial Recognition