Deep Dive into Facial Recognition

1. F
Facial Recognition Technology
Past the Snapchat Fad and Into the Future of Profile Matching

2. What is facial recognition?
Facial Recognition
A way of recognizing a human face
through technology. The system uses
biometrics to map facial features from a
photograph or video
Biometrics
A technical term for body measurements
and calculations. It refers to metrics
related to human characteristics
Biometrics functions as unique identifiers
include fingerprints, hand geometry,
earlobe geometry, retina and iris patterns,
voice waves, DNA, and signatures. The
oldest form of biometric verification is
fingerprinting
How does it work?
Potential Threat
The facial recognition system uses computer algorithms to identify signatures and
details of a person’s face, including the shape of the mouth or the distance
between two eyes
Next, the details are turned into a mathematical representation and composed of a
database of known faces. At least 117 million Americans have images of their faces
in one or more police databases. FBI has access to 412 million images for searches
In the end, a determination is made. One’s faceprint will match that of an image in
a facial recognition system database
Facial recognition may be unreliable and is prone to misidentification of somewhat
similar faces. The FBI has admitted that its facial recognition systems are not
accurate enough to reliably match multiple photos of the same identity.
Thus, facial recognition technology is still in its infancy and has a long road of
development ahead before it can be safely implemented in critical societal
functions.

3. Implementations of Facial Recognition
China Southern Airlines
&
British Airways
China Southern Airlines uses the
facial recognition technology for
passengers to get through identity
verification and board their planes
within seconds by simply having their
faces scanned at the boarding gates
British Airways uses Biometric Gates
for domestic UK flights. The
technology is built into mobile phones
and allows customers to pass through
by recognizing their unique facial
features
Apple
Apple acquired Emotient in 2016, a
startup that uses AI to read people’s
emotions by analyzing facial
expressions.
With the facial recognition
technology, Apple's iPhone X added
an animated emoji feature known as
Animoji. This responds to facial
expressions via the iPhone X camera,
to animate various 3D animated
emojis that can be sent as a video file
with sound.
Helping Faceless
The company’s mission is to reunite
missing children with their parents.
Many children are kidnapped for
various reasons and never get home.
Helping Faceless is on a mission to
change that by matching a photo of
missing children to real children by
using facial recognition. Users take a
photo of a child who is alone, upload
it to the app, and enter the date and
location. Users can also verify
pictures with children they may have
seen to better progress the facial
recognition matching.

4. Future Development
Emotion Detection
The next big thing in facial recognition, with the promise, that it’s not only possible
to identify an individual, but also interpret how they’re feeling. In the future, this
technology can be used in therapies or the mental wellness industry; doctors can
detect how patients feel and treat them accordingly
Age Detection
Age detection algorithms can be useful in retail environments, flagging up
warnings to shop assistants if someone is too young to buy certain products. With
accurate age detection, retailers can better maintain their legal responsibilities
while reducing the potential to offend customers
Secure Payments
Future systems will allow payments to be made more securely. China is currently
the leader of facial recognition of mobile payments; in 2017, Alibaba (Alipay) closed
a $277 million deal with SenseTime, a startup that uses AI and facial recognition
technology
Improved Security and Policing
Facial recognition can be a big part of a modern company’s security strategy. In the
future, the power behind facial recognition systems will be able to do far more. For
example, automatic monitoring will be able to spot shoplifters at work or those not
scanning items at self-checkouts in supermarkets