Facial Recognition: Uses, Advantages & Disadvantages
How does facial recognition work? Face detection is necessary for security purposes. Click here for a detailed guide on face recognition meaning, advantages & disadvantages!
Biometric technologies trace back their origins over a century back. Today, it has made a comeback largely due to modern societal ills and the growing need for national security. The not-so-recent impetus was 9/11 when face recognition– the most popular in the biometric technology family saw renewed demand and rapid adoption.
If you are unversed, here’s a simple version for you by the Cambridge dictionary: “facial recognition is a technology that makes it possible for a computer to recognize a digital image of someone’s face.” Advanced technologies like AI have increased the accuracy of face recognition systems, making a case for its wider acceptance as a primary tool for security, fraud prevention, and a host of surveillance activities, among others. Owing to its growing usage, the global facial recognition market size is forecast to hit USD 8.5 billion by 2025.
How does Facial Recognition work?
Face detection technology primarily determines whether the images match the facial features of an individual. By capturing, analyzing, and subsequently comparing, the numerous patterns of an individual’s face, using facial recognition technology (FRT), the process is concluded.
The three-step process comprising i) face detection, ii) face capture, and lastly iii) face match, are the essentials even though the facial reader technology may vary.
Face identification is based on the 1:N principle, where an image match in the database confirms the identity of an individual.
The accuracy of face recognition algorithms is difficult to assess. However, according to the US-based NIST (National Institute of Standards and Technology), the software used in facial recognition technologies can be evaluated based on two classes of error: false positives and false negatives.
A false positive result by the software denotes that it wrongfully considered photos of two different individuals to show the same individual. A false negative on the other hand means the software is unable to match two photos.
What’s Facial Recognition used for?
The application of facial recognition has surged over the years beyond unlocking the phone. From financial checks to security and much more, the recognition system now plays a pivotal and strategic role in both the private and public sectors. The uses vary but some of the most commonly observed applications include premises such as:
- Airports: Facial recognition systems are used to monitor passengers and people in airports.
- Financial services: The technology is also used for financial services in the public domain for subsidy disbursal, grants, etc, and in the private sector for digital payments, account access, and opening.
- Retailers: The combined use of surveillance cameras and facial recognition to scan shoppers is becoming commonplace now.
- Mobile phones: Apple’s face identification helps to authenticate the owner of the device. As per the phone maker, the possibility of an unknown face accessing your phone by unlocking is about one in 1 million.
- Social media: Facial image recognition by popular social media websites to recognize photos is well known.
- Law enforcement and policing services: From the FBI to local police departments and law enforcement agencies, this face finding and face detection technology is leveraged by everyone.
In a recent study to analyze how widespread is the use of facial recognition technology in different countries across government, police, airports, schools, banking, workplaces, and on buses and trains it was found that only 6 countries (among 100) had no evidence of facial recognition.
*Datawrapper automatically includes French Guiana as part of France's statistics but some factors are likely to be different here and haven't been covered in our research.
(Source: Comparitech)
Some of the key findings comprise:
- 7 in 10 governments are using facial recognition technology on a large scale.
- Nearly 80% of countries use facial recognition in banking and finance.
- Almost 60% of countries have the FRT set up in airports.
The top three countries with the most widespread facial recognition technology use are China, Russia, and the UAE.
The Pros And Cons Of Facial Recognition Technology
With the surging usage of facial recognition technology in everyday life, the awareness among the masses is increasing by the day. Not surprisingly, there has been both a backlash and support for the system. To understand this better, let’s look at the pros and cons of FRT.
The Pros:
- Improved security: The convenience and accuracy afforded by facial recognition to secure borders, and prevent criminal activities is paramount.
- Checking crime: From law enforcement to police, this is a favored tool to keep a check on unwarranted and criminal activities.
- Effortless integration: As an added advantage, most of the latest facial recognition software in the marketplace integrates easily with security systems.
- Usability and convenience: The ease of use granted by the software provides the convenience to skim through millions of faces in a few seconds. The whole process makes face identification seamless.
- Better accuracy: Over time, the FRT technology has evolved to give better matches with higher accuracy with the best-of-the-breed systems having an error rate of 0.08%.
The Cons:
- Breach of privacy: Probably the most debatable among the lot, breach of privacy has attracted a lot of attention of late. The technology is used to capture both criminals and private citizens often without consent, causing concerns among the wider public.
- Data storage: The use of AI in facial recognition means making provision for large data storage. The AI relies on machine learning to train itself, and the accuracy can only be improved with adequate learning.
- Error and bias: Some research studies have cast aspersions on the accuracy of face recognition technology citing divergent error rates across demographic groups.
What’s The Difference Between Face Detection Vs Face Recognition?
Face detection is the first step in face recognition but is oft mistaken and lumped together with the latter. Face detection is the ability of the software to detect if a human face is present or not. The detection process begins with the analysis of photos with algorithms designed to find a facial coordinate match. The software just looks for the image, separating it from the background.
Face recognition is the comprehensive process of comparing the image of an individual in a database to find a match. The database is built with machine learning over time using facial recognition technology.
- Face detection is the basic match to identify the facial features of an individual, however, the software does not recognize if the face is distinct from others.
- It does not memorize or save the data for future matches.
- Face detection only detects the presence of the person.
Face detection is used in various consumer goods such as smart TVs and cameras, and activities such as marketing and advertising campaigns.
HyperVerge And Face Recognition: Why Should You Switch To HyperVerge
In times of dwindling trust, it is imperative to have trustworthy technology by your side. Finding a vendor of your choice should be based on an objective study of the needs. As per Gartner, most buyers’ buying decisions are influenced by three factors: price; ease of implementation, and references from clients with a similar profile.
It is however important to balance the competing demands by assessing the full range of capabilities. A good solution reduces the cost as well as the complexity of multiple vendor integrations. A facial recognition solution must be robust and qualify the following:
- Quality certifications (ISO ISO-30107 and NIST)
- Security and compliance (SOC 2)
- Privacy and law (GDPR readiness)
HyperVerge is a market leader in AI-based facial recognition technology. The recent “1: N identification” NIST rankings place HyperVerge on the leaderboard. Across all geographies, HyperVerge is ahead of its competition in accuracy. The FNMR, if any, is below 1% across races. One of the best liveness checks and device compatibility are just add-ons that favor HyperVerge.
Conclusion
Facial recognition, whether you like it or not, is here to stay. It is a practical and convenient way of safeguarding the public and private interests. FRT software makers are today advancing their technology consistently to provide better results in not-so-conducive environments.
Facial recognition and facial authentication, within the biometric technologies space, are the blue-eyed solutions. The inherent and multiple benefits of today’s advanced facial recognition solutions cannot be overlooked. Facial recognition supplements human decision making to make the right judgement. A clear understanding of the technology may allay many concerns that surround the technology.
