Facial Recognition

Facial recognition is an AI-driven method of verifying the identity of an individual by using their facial features. To identify people in photos, videos, or in real-time is the main use of a Facial recognition system. It is widely used for security purposes.

How does facial recognition work?‍

Technologies for this may vary, but here are the basic steps to it:

Step 1: From a photo or video a picture of your face is captured. Your face might be shown alone or in a crowd. It may show you looking straight ahead or turned to one of your sides.

Step 2: The geometry of your face is been read thoroughly by the Facial recognition software. Some of the key factors include - the distance between your eyes and the distance between your forehead and chin. The software identifies significant facial landmarks (some systems identify 68 of them)  that play an important role in distinguishing your face from others. The result: your facial signature gets prepared digitally.

Step 3: Your facial signature is now a derived mathematical formula which is then compared to a database of known faces. At least 117 million Americans have images of their faces in one or more police databases. According to a May 2018 report, the American FBI has access to 412 million facial images for investigative purposes. 

Step 4: A determination is made out of it. Your faceprint is made to match that of an image in the system database.

Who uses facial recognition?

A lot of people and organizations use this software system and for a lot of different purposes. Here’s an example:

(i) The U.S.A. government at airports.

Automatic Facial recognition systems can monitor people coming and stepping into airports. The Department of Immigration agency has used the technology to spot those who have overstayed their visas or could also be under criminal investigation. Customs officials at Washington Dulles International Airport made their first arrest using identity verification in August 2018, catching an impostor trying to enter the country.

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(ii) Mobile phone makers in products.

Apple first used identity verification to unlock its iPhone X and continues the same with the iPhone XS. Face ID authenticates — it makes sure you’re indeed yourself after you attempt to access the device. Apple says the possibility of a random face unlocking your phone is about one in 1 million.

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(iii) Colleges within the classroom.

The software can, in essence, take a roll call. If you choose to bunk class, your professor could know.

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(iv) Social media companies on websites.

Facebook uses an algorithm to identify faces once you upload a photograph to its platform. The social media company asks if you would like to tag people in your photos. If you say yes, it creates a link to their profiles. Facebook can recognize faces with 98 percent accuracy.

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(v) Businesses at entrances and restricted areas.

Some companies have traded in security badges for identity verification systems. Beyond security, it may be a technique to urge some face time with their bosses.

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(vi) Religious groups at places of worship.

Churches have used automatic Facial recognition to scan their congregations to determine who’s present. It’s an honest effort to track regulars and not-so-regulars,  to further help tailor donation requests.

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(vii) Retailers in stores.

Retailers can combine surveillance cameras and biometric authentication to scan the faces of shoppers. One goal: Identifying suspicious characters and potential shoplifters.

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(viii) Airlines at departure gates.

You would possibly be conversant about having an agent scan your boarding card at the gate to board your flight. Although, a minimum of one airline scans your face as well.

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(ix) Marketers and advertisers in campaigns. 

Marketers often consider demographics and psychographics like gender, age, and ethnicity when targeting certain groups for a product or idea. Automatic Facial recognition is often accustomed to define those audiences even at an event like a concert.

What are the Threats Posed By Facial recognition ?

• Security: Your facial data will be collected and stored, often without your permission. It's possible hackers could access and steal that data.
  

• Prevalence: Identity verification technology is becoming more widespread. Meaning your facial signature could find itself in a whole lot of places. You most likely won’t know who has access to that.
  

• Ownership: You own your face — the one atop your neck — but your digital images are different. You will have given up your right to ownership once you’ve signed off on the terms and conditions of a social media network. Or even if someone tracks down images of you online and sells that data.
  

• Safety: Automatic Facial recognition may lead to online harassment and stalking. How is this possible? As an example, someone could take a picture of you on a subway or another public place and uses Facial recognition software to seek out exactly who you're.
  

• Mistaken identity: Say, as an example, law enforcement uses biometric authentication to spot someone who robbed a corner store. Biometric authentication systems might not be one hundred percent accurate. So there is a possibility that they may suspect the wrong person.
  

• Basic freedoms: Government agencies could have the flexibility to trace you. What you are doing and where you go might not be private. It could become impossible to stay anonymous.

Which algorithm is used in Facial recognition?

When we discuss automatic Facial recognition tools, some recognition algorithms include principal component analysis using eigenfaces, linear discriminant analysis, elastic bunch graph matching using the Fisherface algorithm, the hidden Markov model, the multilinear subspace learning using tensor representation, and therefore the neuronal motivated dynamic link matching. There are others too, but their use depends on your aim of using the system.

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What is the difference between Face detection and Facial recognition? 

One of the foremost significant applications of face detection, however, is automatic Facial recognition. It describes a biometric technology that goes way beyond recognizing when somebody's face is present. It actually attempts to determine whose face it is. This method works by employing a computer software application that captures a digital image of an individual’s face (sometimes taken from a video frame) and compares it to photographs in every database of stored records. While biometric authentication isn’t 100% accurate, it can very closely and accurately determine when there's a powerful chance that a person’s face matches someones within the database.