Stories

Face Off / Face On

Do androids dream of electric lipstick? As facial recognition technology evolves, so does the role of make up. Darren Black explores the faces we make-up, the technology that seeks to unmask us and the next chapter of disruptive beauty.

Words
DARREN BLACK
Photography
SERENA BECKER
Beauty
PATRICK GLATTHAAR

I love seeing women put their makeup on on the tube, I get to voyeuristically (& for the most part, furtively) watch as they reach for the old makeup bag and build their “look” – I find it fascinating & somewhat amazing that women can deftly match a pair of eyebrows on a moving train. For most, it’s a case of “shake what yo mama gave ya but gimme me a red lip or signature eyeliner”, but for some it’s more of a case of “take this plain Jane and transform her into a super vixen”.

I know it sounds gross, but really come on, who doesn’t like to creep on strangers in a public place… actually saying that aloud does sound odd… aaanywayyy, a few months ago I had the “pleasure” of watching a woman board the carriage and sit in the only empty seat directly opposite me.  She was very average (I’m genuinely not being disparaging): plain white skin, a few pimples, puffy just woken-up eyes, regular lips, brown hair to the shoulders, high street blouse/skirt combo, shoes from office, handbag from Zara – quite trendy but not ostentatiously so. She could have been 23 or 27 who knows? She was heading towards the city so I’m guessing she worked in a corporate office. So she sits down and reaches into her handbag and pulls out a massive makeup bag and gets to work.  She begins by smearing on really really pale foundation, blending it all the way into her ears. 

 

Computers don’t have memory sense so they rely on coding to statistically ascertain a description of someone. Scanning faces and gait, computers build a database of characteristics that are applied to us to enable recognition.  

Then goes on a thick stick of concealer under the eyes, down the centre of the nose & on the lips.  Next she takes what looks like a dark brown concealer stick and rubs it down the sides of the nose and along the jawbone, proceeding to draw two lines on the sides of her face sucking in her cheeks to get the placement correct. With a large blusher brush, she smudges all of the pale and dark lines together. Leaving that to set, she dabs the first layer of powder on and gets to work on her eyes. With liquid eyeliner she wings both of her eyes perfectly (the train is moving, remember) and applies a cut crease and some kind of creamy eyeshadow. The eyebrows get pencilled on in a gentle “Disney-Step-Mother” arch.  On the lip she overlines the concealer with brown pencil and first starts with a mid brown lipstick, then a light brown lipstick on the middle part of the mouth and finishes with a gloss.  She dusts the top of her cheekbone with highlighter and then applies a second layer of loose powder to set everything. This operation was conducted in the kind of small compact mirror that comes with pressed powder on a tube that is hurtling toward the city along wonky tracks… Some dry shampoo in the crown of the hair is enough to give it traction to create a “teased bed head bob” and a pair of small dangly earrings go in the ears. This woman has transformed herself in the time it takes to travel from Oxford Circus to Bank (I stayed on past my stop.) She clearly has this routine down to a fine art.  

The overall effect was quite astonishing – she had gone from being anyone to someone – gone were the pimples, the eye puffs, the regular lips, only to be replaced by porcelain glam with a bee stung pout. To say this was a transformation would be an understatement – this was an ANTM makeover & my girl had won the challenge!

This episode stuck with me for a while until then next time I was sitting opposite a different woman: same work uniform, same beauty regime, same destination. I started to think about the masks we all wear to work and how transformative we have to be to appear professional. Would these women be taken more or less seriously if they arrived at work each day bare faced? Does a full face of makeup mean that you’re ready for business? Does makeup have the responsibility of creating or enhancing beauty? Or both? 

The facial recognition market is expected to grow to £6 billion in 2022 from £3.13 billion in 2017. That’s because Facial Recognition has all kinds of commercial applications - it can be used for everything from surveillance to marketing.  

The women that I see on the tube are certainly transforming themselves with a mask so clever that they still look like themselves but are simultaneously unrecognisable. I wonder though: with makeup that transformative, does their iPhone open with their face or are they still on fingerprint technology?

I don’t wear makeup but I do wear glasses and because I’m an obsessive collector, I have several pairs. When I’m wearing the thicker rimmed face furniture my iPhone doesn’t recognise me, so I have to do my Eric Morecambe impression and let the phone know who I am by pushing them up my forehead and looking into the camera “It’s me, Darren!”  I also don’t look like my passport anymore so I can’t fast track through the Facial Recognition booths at the airport. I have to stand in line and have my passport held up to my face by a real life human while they ascertain if the slender guy with a full head of hair in the tiny photo is actually me.

As babies we are programmed to recognise our mothers by touch within hours of birth and within three days we know her smell, by one week, we recognise her face.  I suppose that’s what they call one of the human conditions. Computers don’t have memory sense so they rely on coding to statistically ascertain a description of someone. Scanning faces and gait, computers build a database of characteristics that are applied to us to enable recognition.  

According to The Telegraph (Oct 18), Facial Recognition will soon be used in British shops for the first time to judge how old customers are at self-checkout machines when they buy age-restricted items, it is understood following a deal with the company that makes the tills for Tesco and Asda. NCR, who make the software and hardware for self-check machines for the majority of the UK’s supermarkets, will integrate a camera that will estimate the age of shoppers when they are buying alcohol and cigarettes.   

Facial Recognition systems use biometrics to map facial features from a photograph or video. The computer then compares the information with a database of known faces to find a match. This might be able to help verify personal identity, but it also raises privacy issues.  The facial recognition market is expected to grow to £6 billion in 2022 from £3.13 billion in 2017. That’s because Facial Recognition has all kinds of commercial applications – it can be used for everything from surveillance to marketing.  

So how does facial recognition work? Algorithmically not too dissimilar to super recognisers (it is estimated that 1 to 2% of the population are super recognisers who can remember 80% of faces they have seen – most people can only remember about 20% of faces. Super recognisers can actually match faces better than computer recognition systems in some circumstances.)  Technologies vary, but here are the basic steps:

Step 1: A picture of your face is captured from a photo or video. Your face might appear alone or in a crowd. Your image may show you looking straight ahead or nearly in profile.
Step 2: Facial Recognition software reads the geometry of your face. Key factors include the distance between your eyes and the distance from forehead to chin. The software identifies facial landmarks — one system identifies 68 of them — that are key to distinguishing your face. The result: your facial signature.
Step 3: Your facial signature — a mathematical formula — is compared to a database of known faces.
Step 4: A determination is made. Your faceprint may match that of an image in a facial recognition system database.

 

So what’s the issue?

Security: Your facial data can be collected and stored, often without your permission. It’s possible hackers could access and steal that data.
Prevalence: Facial recognition technology is becoming more widespread. That means your facial signature could end up in a lot of places. You probably won’t know who has access to it.
Ownership: You own your face but your digital images are different. You may have given up your right to ownership when you signed up on a social media network.
Safety: Facial recognition could lead to online harassment and stalking – Facebook has a 98% accuracy rate at recognising faces.  

One way of protecting yourself against facial recognition systems is by using disruptive makeup (note to my gals riding the 8am tube.) Specifically something called CV Dazzle: Computer Vision Dazzle also known as CV Dazzle, Dazzle Makeup, or Anti-Surveillance Makeup, is a type of camouflage used to hamper facial recognition software, inspired by Razzle Dazzle camouflage on warships in World War using cubist-inspired designs to break apart the visual continuity of a battleship and conceal its orientation and size.

CV Dazzle combines stylised makeup, asymmetric hair, and sometimes infrared lights built in to glasses or clothing to break up detectable facial patterns recognised by computer vision algorithms in much the same way that warships contrasted colour and used sloping lines and curves to distort the structure of a vessel. It has been shown to be somewhat successful at defeating face detection software in common use, including that employed by Facebook. CV Dazzle attempts to block detection by facial recognition technologies such as DeepFace which relies on “the identification and spatial relationship of key facial features, like symmetry and tonal contours, by creating an ‘anti-face.'” It uses occlusion, covering certain facial features; transformation, altering the shape or colour of parts of the face; and a combination of the two.  

CV Dazzle explores how fashion can be used as camouflage from face-detection technology, the first step in automated face recognition. 

One of the prominent makeup artists employing this technique is Adam Harvey. According to Harvey, CV Dazzle explores how fashion can be used as camouflage from face-detection technology, the first step in automated face recognition.  Just scrolling through Instagram and looking at some of the makeup artists and queer performers on there illustrates just how far CV Dazzle has come: @isshehungry, @matieresfecales, @parmaham, @salvjiia et al are all practitioners of a kind of CV Dazzle – ostensibly hiding in plain sight. Even Bjork has been known to dabble in anti-face as part of her performances. Slava Tsukerman’s 1982 dystopian film Liquid Sky about a model who kills men with her pussy has most of the characters sporting avant garde cubist makeup looks referenced by Pat McGrath for her inspiration on the Louis Vuitton Resort ’16 collection. Similarly, Jordan as Amyl Nitrate in Derek Jarman’s 1978 film Jubilee “anti-faced” herself before we even had technological concerns over the ownership of our faces. Adam Ant too, Pete Burns, Toyah Wilcox all disrupted their natural beauty in the political act of being punk. The punk movement was about active disruption – something we’re seeing a return of in certain subcultures currently, which of course, I applaud, and whilst I enjoy traditional values of beauty, I do love it when I see someone who’s gone a bit bonkers with their money-maker: Pierpaolo Piccioli presented his Valentino Haute Couture collection in Beijing on models with silver faces. Kabuki Starshine & Bob Recine created makeup & hair looks that were very disruptive for a Collina Strada shoot in Vogue but surely at the current rate of technological advancement, facial recognition systems will figure out a way of navigating disruption and find order in the chaos of war paint.

I suppose for me this poses the real question: does Facial Recognition technology actually work or is the human eye still the best computer for truly seeing us?  Well, the proof, as they say, is in the pudding. But if the proof of the pudding is in the eating: we recognise people not just with how we see them but also, what they remind us of, how they make us feel, how they sound and walk. It’s a heady mix of olfactory and memory senses that are triggered.  As a photographer, I’ve never forgotten a face I’ve shot – I have my own personal database and for every photograph I’ve taken I can remember the story my model was telling me, their laugh, the music we listened to and how they made me feel and that’s good enough for me. 


Photography: Serena Becker
Beauty: Patrick Glatthaar
Casting: Kyra Wilhelmseder  @Kyrasophie
Models: Begana @beg__gana__, Enrico @enr.arn, Stella @stellastrophe; Yannick, Hanna G. and Yousif @youee