like behind the scenes?

JOSS: Hmm, I have no idea.

JOE: Well do you think you can find out?

JOSS: You got it!

These are what Snapchat calls their lenses, but everyone else calls filters.

They are very silly but the engineering behind them is serious.

JOSS: Oh my god.

The technology came from a Ukrainian startup called Looksery

which Snapchat acquired in September 2015 for a $150 million dollars.

That's reportedly the largest tech acquisition in Ukrainian history.

Their augmented reality filters tap into the large and rapidly

growing field of "computer vision" --

those are applications that use pixel data from a camera in order to identify objects

and interpret 3D space. Computer vision is how you can deposit checks,

it's how Facebook knows who's in your photos, how self-driving cars can avoid

running over people and how you can give yourself a doggy nose.

So how do snapchat filters work? They wouldn't let us talk to any of the Looksery

engineers but their patents are online.

The first step is detection. How does the computer know which part of an image is

a face?

This is something that human brains are fantastic at. Too good even.

But this is what a photo looks like to a computer. If all you have is the data for

the color value of each individual pixel, how do you find a face?

Well the key is looking for areas of contrast, between light and dark parts of

the image. The pioneering facial detection tool is called the

Viola-Jones algorithm.

It works by repeatedly scanning through the image data calculating the

difference between the grayscale pixel values underneath the white boxes and

the black boxes. For instance, the bridge of the nose is usually lighter than the surrounding area on both sides,

the eye sockets are darker than the forehead, and the middle of the forehead

is lighter than the size of it.

These are crude test for facial features, but if they find enough matches in one

area of the image,

it concludes that there is a face there. This kind of algorithm won't find your

face if you're really tilted or facing sideways, but they're really accurate for

frontal faces, and it's how digital cameras have been putting boxes around

faces for years. But in order to apply this virtual lipstick, the app needs to

do more than just detect my face.

It has to locate my facial features.

According to the patents, it does this with an “active shape model” -- a statistical

model of a face shape that's been trained by people manually marking the

borders of facial features on hundreds, sometimes thousands of sample images.

The algorithm takes an average face from that trained data and aligns it with the

image from your phone's camera, scaling it and rotating it according to where it

already knows your face is located.

But it's not a perfect fit, so the model analyzes the pixel data around each of the points,

looking for edges defined by brightness and darkness. From the training images,

the model has a template for what the bottom of your lips should look like,

for example, so it looks for that pattern in your image and adjust the point to match it.

Because some of these individual guesses might be wrong,

the model can correct and smooth them by taking into account the locations of all

the other points. Once it locates your facial features, those points are used as

coordinates to create a mesh.

That's a 3D mask that can move, rotate, and scale along with your face as the

video data comes in for every frame and once they've got that, they can do a lot with it.

They can deform the mask to change your face shape, change your eye color,

add accessories, and set animations to trigger when you open your mouth

or move your eyebrows.

And like the IOS app Face Swap Live, Snapchat can switch your face with a

friend's, although that involves a bunch more data.

The main components of this technology are not new. What's new is the ability to

run them in real time, from a mobile device. That level of processing speed is

a pretty recent development.

So why go through all this trouble just to give people a virtual flower crown?

Well Snapchats sees a revenue opportunity here. In a world that's

flooded with advertisements,

maybe the best hope that brands have to get us to look at their ads... is to

put them on our faces.

Facial detection has a creepy side too, particularly when it's used to identify you by name.

Both the FBI and private companies like Facebook and Google are massing huge

databases of faces and there's currently no federal law regulating it.

So some privacy advocates have come up with ways to camouflage your face from

facial detection algorithms.

It's actually illegal in a lot of places to wear a face mask in public,

so this project by artist Adam Harvey suggest some things that you can do with

your hair and your makeup that can, for now, make your face Invisible to computers.