At first glance, dazzle seems an unlikely form of camouflage, drawing attention to the ship rather than hiding it, but this technique was developed after Allied navies were unable to develop effective means to hide ships in all weather conditions.
The British zoologist John Graham Kerr, who first applied dazzle camouflage to British warships in WWI, outlined the principle in a letter to Winston Churchill in 1914 explaining that disruptive camouflage sought to confuse, not to conceal, “It is essential to break up the regularity of outline and this can be easily effected by strongly contrasting shades … a giraffe or zebra or jaguar looks extraordinarily conspicuous in a museum but in nature, especially when moving, is wonderfully difficult to pick up.”
The anti-surveillance state: Clothes and gadgets block face recognition technology and make you digitally invisible
Janet Burns, AlterNet
26 Apr 2015 at 18:52 ET
CV Dazzle designs for hair and makeup obscure the eyes, bridge of the nose and shape of the head, as well as creating skin tone contrasts and asymmetries. Facial-recognition algorithms function by identifying the layout of facial features and supplying missing info based on assumed facial symmetry. The project demonstrates that a styled “anti-face” can both conceal a person’s identity from facial recognition software (be it the FBI’s or Facebook’s) and cause the software to doubt the presence of a human face, period.
Harvey’s work is focused on accessibility in addition to privacy. “Most of the projects I’ve worked on are analog solutions to digital challenges,” he said. His hair and makeup style tips – a veritable how-to guide for how to create “privacy reclaiming” looks at home – are “deliberately low-cost.” His current project – software to “automatically generate camouflage…that can be applied to faces” – will allow a user to “create [their] own look and guide the design towards [their] personal style preferences.”
Other low-tech protections against widespread surveillance have been gaining ground, too. Though initially designed as a tongue-in-cheek solution to prying eyes and cameras, Becky Stern’s Laptop Compubody Sock offers a portable, peek-free zone to laptop users, while the CHBL Jammer Coat and sold-out Phonekerchief use metal-infused fabrics to make personal gadgets unreachable, blocking texts, calls and radio waves. For people willing to sport a bit more hardware in the name of privacy, the Sentient City Survival Kit offers underwear that notifies wearers about real-life phishing and tracking attempts, and its LED umbrella lets users “flirt with object tracking algorithms used in advanced surveillance systems” and even “train these systems to recognize nonhuman shapes.”
Earlier this year, antivirus software leaders AVG revealed a pair of invisibility glasses developed by its Innovation Labs division. The casual looking specs use embedded infrared lights “to create noise around the nose and eyes” and retro-reflective frame coating to interfere with camera flashes, “allowing [the wearer] to avoid facial recognition.” In early 2013, Japan’s National Institute of Informatics revealed a bulky pair of goggles it had developed for the same purpose.
A spokesperson for Innovation Labs claims its glasses represent “an important step in the prevention against mass surveillance…whether through the cell phone camera of a passerby, a CCTV camera in a bar, or a drone flying over your head in the street.” Innovation Labs says that, with a person’s picture, facial recognition software “coupled with data from social networking sites can provide instant access to the private information of complete strangers. This can pose a serious threat to our privacy.” Though AVG’s glasses are not scheduled for commercial release, Innovation Labs said that individuals can take a number of steps to prevent their images from being “harvested”:
“First and foremost, make sure you’re not allowing private corporations to create biometrics profiles about you. When using social networks like Facebook, be aware that they are using facial recognition to give you tag suggestions. Facebook’s DeepFace was already tested and trained on the largest facial dataset to-date (an identity labeled dataset of more than 4 million facial images belonging to thousands of identities).”