In a pre-print paper titled “Novel AI Camera Camouflage: Face Cloaking Without Full Disguise,” David Noever, chief scientist, and Forrest McKee, data scientist, describe their efforts to baffle face recognition systems through the minimal application of makeup and manipulation of image files.
Noever and McKee recount various defenses that have been proposed against facial recognition systems, including CV Dazzle, which creates asymmetries using high-contrast makeup, adversarial attack graphics that confuse algorithms, and Juggalo makeup, which can be used to obscure jaw and cheek detection.
And of course, there are masks, which have the advantage of simplicity and tend to be reasonably effective regardless of the facial recognition algorithm being used.
But as the authors observe, these techniques draw attention.
“While previous efforts, such as CV Dazzle, adversarial patches, and Juggalo makeup, relied on bold, high-contrast modifications to disrupt facial detection, these approaches often suffer from two critical limitations: their theatrical prominence makes them easily recognizable to human observers, and they fail to address modern face detectors trained on robust key-point models,” they write.
“In contrast, this study demonstrates that effective disruption of facial recognition can be achieved through subtle darkening of high-density key-point regions (e.g., brow lines, nose bridge, and jaw contours) without triggering the visibility issues inherent to overt disguises.”
Image from the pre-print depicting man’s face with Darth Maul-style makeup … Click to enlarge
The research focuses on two areas: applying minimal makeup to fool Haar cascade classifiers – used for object detection in machine learning, and hiding faces in image files by manipulating the alpha transparency layer in a way that keeps faces visible to human observers but conceals them from specific reverse image search systems like BetaFaceAPI and Microsoft Bing Visual Search.
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“Despite a lot of research, masks remain one of the few surefire ways of evading these systems [for now],” she said. “However, gait recognition is becoming quite powerful, and it’s also unclear if this will supplant face recognition. It is harder to imagine practical and effective evasion strategies against this technology.”
Source: Subtle makeup tweaks can outsmart facial recognition • The Register
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