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Camouflage from Computer Vision
January 6, 2012 | Hogan Keyser
by Adam Harvey via CVDazzle.com --
CV Dazzle(TM) is camouflage from computer vision (CV). It is a form of expressive interference that combines makeup and hair styling (or other modifications) with face-detection thwarting designs. The name is derived from a type of camouflage used during WWI, called Dazzle, which was used to break apart the gestalt-image of warships, making it hard to discern their directionality, size, and orientation. Likewise, the goal of CV Dazzle is to break apart the gestalt of a face, or object, and make it undetectable to computer vision algorithms, in particular face detection.
Because face detection is the first step in automated facial recognition, CV Dazzle can be used in any environment where automated face recognition systems are in use, such as Google's Picasa, Flickr, or Facebook (see CV Dazzle vs PhotoTagger by Face.com).
This project began as a thesis proposal at the Interactive Telecommunications Program at New York University in the spring of 2010 with the primary objective of thwarting face detection under the guise of high-fashion aesthetics. While there are several obvious approaches to hiding from face detection, some of these can be dismissed. Sunglasses, for example, are a known occlusion which some algorithms account for. And, though functionally effective, wearing masks in public can be illegal. Hoods are popular and effective but make the wearer's intent to hide too obvious. As an alternative, this project explores ways of hiding in plain sight using ambiguously deceptive fashion.
CV Dazzle opposes the mainstream push towards the widespread adoption of face recognition in order to protect privacy. As the usefulness and popularity of facial recognition grows in commerce and security (currently it's the fastest growing sector of biometrics ), so will the value of privacy. The objective of CV Dazzle is to adapt to our new environment and explore ways of communicating with machines to control our privacy in public.
There is a strong emphasis towards radical-neutrality. The designs used in the first several looks are inspired by both tribal paint and high-fashion aesthetics from the club scene in London. In fact, photos from both were incorporated into the testing algorithms. Surprisingly, many of the more eccentric looks did not fool the face detection algorithms.
To design the looks at left, software was developed that combines interactive drawing and genetic algorithms to detect vulnerabilities in the face detection process. By understanding how face-detection algorithms work, an anti-face can be constructed and used as a guide for creating makeup and hair-styling that foils the face detection process. As a result, your face becomes undetectable to machines yet retains some level of legibility to humans.
CV Dazzle is a work in progress. As computer vision matures so will this project.
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