Facial recognition software compares two images of a person’s face. One image is recent, while the other is stored in a database. Algorithms try to match the two images. When successful, the software can identify a person from a photo.
What is Facial Recognition?
Facial recognition is a method of identifying or verifying an individual’s identity using their face. These systems can identify people in photos, videos, or in real-time.
Facial recognition falls under the category of biometric security. Other types of biometric software include voice recognition, fingerprint recognition, and retina or iris recognition. While this technology is primarily used for security and law enforcement, its applications are expanding into other areas.
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How does facial recognition work?
Many people are familiar with facial recognition technology through FaceID, used to unlock iPhones, although this is just one application of facial recognition. Typically, this technology does not rely on a massive database of photos to determine an individual’s identity; it simply identifies and recognizes one person as the device’s owner, restricting access to others.
Beyond unlocking phones, facial recognition works by matching faces of people walking past special cameras to images on a watch list. These watch lists can include pictures of anyone, even those not suspected of any wrongdoing, with images sourced from various places, including social media accounts. Facial recognition systems can vary, but generally, they operate as follows:
Step 1: Face detection
The camera detects and locates a face in the image, whether the person is alone or in a crowd. The face may be looking straight ahead or in profile.
Step 2: Face analysis
The software captures and analyzes the image of the face. Most facial recognition technology relies on 2D images because they can more easily match public photos or those in databases. The software measures the geometry of the face, including the distance between the eyes, the depth of the eye sockets, the distance from forehead to chin, the shape of the cheekbones, and the contour of the lips, ears, and chin. These facial landmarks are key to distinguishing one face from another.
Step 3: Converting the image to data
The face capture process converts the analog information (a face) into a set of digital data based on facial features. This analysis is turned into a mathematical formula known as a faceprint. Like unique thumbprints, each person has their own unique faceprint.
Step 4: Finding a match
The faceprint is compared against a database of known faces. For instance, the FBI has access to up to 650 million photos from various state databases. On Facebook, any photo tagged with a person’s name becomes part of Facebook’s database, which can also be used for facial recognition. If the faceprint matches an image in the database, a determination is made.
Of all biometric measurements, facial recognition is considered the most natural. This makes sense intuitively, as we usually recognize ourselves and others by faces rather than thumbprints or irises. It is estimated that over half of the world’s population regularly encounters facial recognition technology.
How facial recognition is used
The technology is used for a variety of purposes, including:
Unlocking phones
Many phones, including the latest iPhones, use facial recognition to unlock the device. This technology offers a powerful way to protect personal data, ensuring that sensitive information remains inaccessible if the phone is stolen. Apple claims the chance of a random face unlocking your phone is about one in a million.
Law enforcement
Facial recognition is increasingly used by law enforcement. According to an NBC report, its use is growing among law enforcement agencies in the US and other countries. Police collect mugshots from arrestees and compare them against local, state, and federal face recognition databases. Once an arrestee’s photo is taken, it is added to databases for future criminal searches. Mobile face recognition also allows officers to use smartphones, tablets, or other portable devices to take a photo of a driver or pedestrian in the field and immediately compare it against one or more face recognition databases to attempt identification.
Airports and border control
Facial recognition is common at many airports worldwide. Increasing numbers of travelers hold biometric passports, allowing them to skip long lines and walk through automated ePassport control for faster access to gates. This not only reduces waiting times but also enhances security. The US Department of Homeland Security predicts facial recognition will be used on 97% of travelers by 2023. Besides airports and border crossings, the technology is used to improve security at large-scale events like the Olympics.
Finding missing persons
Facial recognition can help locate missing persons and victims of human trafficking. If missing individuals are added to a database, law enforcement can be alerted as soon as they are recognized by face recognition, whether in an airport, retail store, or other public space.
Reducing retail crime
Facial recognition is used to identify known shoplifters, organized retail criminals, or people with a history of fraud. Photographs of such individuals can be matched against large criminal databases, allowing loss prevention and retail security professionals to be notified when potential threats enter the store.
Improving retail experiences
The technology can enhance retail experiences for customers. For instance, in-store kiosks could recognize customers, suggest products based on purchase history, and provide directions. “Face pay” technology could enable shoppers to bypass long checkout lines with quicker payment methods.
Banking
Biometric online banking benefits from facial recognition. Instead of using one-time passwords, customers can authorize transactions by looking at their smartphone or computer. With facial recognition, there are no passwords for hackers to steal. Even if hackers access the photo database, ‘liveness’ detection—ensuring the biometric sample is from a live person—should theoretically prevent impersonation. This could render debit cards and signatures obsolete.
Marketing and advertising
Marketers use facial recognition to enhance consumer experiences. For example, in a 2017 campaign, DiGiorno used facial recognition to analyze expressions at themed parties to gauge reactions to pizza. Media companies use it to test audience responses to movie trailers, TV characters, and promotional placements. Billboards with facial recognition technology, like those in London’s Piccadilly Circus, can trigger tailored advertisements.
Healthcare
Hospitals use facial recognition to improve patient care. Healthcare providers are testing its use for accessing patient records, streamlining registration, detecting patient emotions and pain, and identifying specific genetic diseases. AiCure has developed an app using facial recognition to ensure people take their medication as prescribed. As biometric technology becomes more affordable, its adoption in healthcare is expected to rise.
Tracking student or worker attendance
Some educational institutions in China use facial recognition to ensure students attend classes. Tablets scan students’ faces and match them to photos in a database to verify their identities. More broadly, the technology can be used for workers to sign in and out of workplaces, allowing employers to track attendance.
Recognizing drivers
According to a consumer report, car companies are experimenting with facial recognition to replace car keys. This technology could replace keys for car access and ignition, and remember drivers’ preferences for seat and mirror positions and radio presets.
Monitoring gambling addictions
Facial recognition can help gambling companies better protect their customers. It enables them to identify registered gambling addicts and track their activity, allowing staff to advise when it’s time to stop. This is especially useful in large, crowded spaces like casinos. Casinos can face hefty fines if gamblers on voluntary exclusion lists are caught gambling.
Examples of facial recognition technology
- Amazon previously promoted its cloud-based facial recognition service, Rekognition, to law enforcement agencies. However, in a June 2020 blog post, the company announced a one-year moratorium on police use of its technology. This pause was intended to allow time for US federal laws to be established to protect human rights and civil liberties.
- Apple uses facial recognition to help users quickly unlock their phones, log into apps, and make purchases.
- British Airways enables facial recognition for passengers boarding flights from the US. Travelers can have their identity verified by a camera scan to board their plane without showing their passport or boarding pass. The airline has used this technology on UK domestic flights from Heathrow and is working towards implementing biometric boarding on international flights from the airport.
- Cigna, a US-based healthcare insurer, allows customers in China to file health insurance claims using a photo instead of a written signature to reduce fraud.
- Coca-Cola has used facial recognition in various ways worldwide, such as rewarding customers for recycling at vending machines in China, delivering personalized ads on vending machines in Australia, and for event marketing in Israel.
- Facebook began using facial recognition in the US in 2010 with its tag suggestions tool, which automatically tagged people in photos. Since 2019, Facebook has made this feature opt-in to enhance privacy. Information on how to opt-in or out of facial recognition can be found on Facebook.
- Google incorporates facial recognition into Google Photos, using it to sort and automatically tag pictures based on the people recognized.
- MAC makeup uses facial recognition technology in some stores, allowing customers to virtually “try on” makeup using in-store augmented reality mirrors.
- McDonald’s has used facial recognition in its Japanese restaurants to assess customer service quality, including analyzing whether employees are smiling while assisting customers.
- Snapchat is a pioneer of facial recognition software, allowing brands and organizations to create filters that mold to the user’s face, resulting in popular features like puppy dog faces and flower crown filters seen on social media.
Advantages of face recognition
Aside from unlocking your smartphone, facial recognition offers several other benefits:
Increased security
Facial recognition can help identify terrorists or other criminals on a governmental level. On a personal level, it can be used as a security tool for locking personal devices and monitoring personal surveillance cameras.
Reduced crime
Facial recognition makes it easier to track down burglars, thieves, and trespassers. The mere presence of a facial recognition system can deter petty crime. Additionally, it benefits cybersecurity, as companies can use facial recognition technology instead of passwords to access computers. This technology is theoretically more secure, as there is nothing to steal or change, unlike passwords.
Removing bias from stop and search
Public concern over unjustified stops and searches is a controversial issue for police. Facial recognition technology could improve this process by singling out suspects in crowds through an automated process, potentially reducing bias and decreasing unnecessary stops and searches of law-abiding citizens.
Greater convenience
As facial recognition technology becomes more widespread, customers will be able to pay in stores using their face instead of using credit cards or cash, saving time in checkout lines. Since facial recognition requires no physical contact, unlike fingerprinting or other security measures, it is particularly useful in the post-COVID world, offering a quick, automatic, and seamless verification experience.
Faster processing
Recognizing a face takes only a second, benefiting companies that use facial recognition. In an era of cyber-attacks and advanced hacking tools, companies need technologies that are both secure and fast. Facial recognition enables quick and efficient verification of a person’s identity.
Integration with other technologies
Most facial recognition solutions are compatible with existing security software and are easily integrated, minimizing the additional investment required to implement it.
Disadvantages of face recognition
While some people do not mind being filmed in public and accept the use of facial recognition where there is a clear benefit or rationale, the technology can provoke strong reactions from others. Some disadvantages or concerns include:
Surveillance
There is concern that combining facial recognition with ubiquitous video cameras, artificial intelligence, and data analytics could lead to mass surveillance, potentially restricting individual freedom. While facial recognition allows governments to track down criminals, it could also enable them to monitor ordinary, innocent people at any time.
Scope for error
Facial recognition data is not infallible and can result in errors, potentially implicating people for crimes they did not commit. Factors such as slight changes in camera angle or appearance, like a new hairstyle, can lead to mistakes. For instance, in 2018, Newsweek reported that Amazon’s facial recognition technology had mistakenly identified 28 members of the US Congress as individuals arrested for crimes.
Breach of privacy
The ethical and privacy implications are highly contentious. Governments have been known to store citizens’ photos without their consent. In 2020, the European Commission considered a ban on facial recognition technology in public spaces for up to five years to develop a regulatory framework to prevent privacy and ethical abuses.
Massive data storage
Facial recognition software relies on machine learning technology, which needs massive data sets to deliver accurate results. Managing such large data sets requires robust data storage solutions. Small and medium-sized companies may lack the resources necessary to store the required data.
Facial recognition security – how to protect yourself
While biometric data is generally considered one of the most reliable authentication methods, it also poses significant risks. If someone’s credit card details are hacked, they have the option to freeze their credit and take steps to change breached personal information. But what recourse do you have if your digital ‘face’ is lost?
Biometric information is increasingly captured, stored, and analyzed worldwide, often by organizations and governments with varying cybersecurity measures. The safety of the infrastructure that holds and processes this data is a growing concern.
As facial recognition software is still relatively new, the laws governing this area are evolving, sometimes lacking clarity. Regular citizens whose information is compromised have limited legal avenues for recourse. Cybercriminals often evade authorities or face consequences years later, leaving victims uncompensated and unsupported.
As facial recognition use expands, so does the potential for hackers to steal facial data for fraudulent purposes.
A comprehensive cybersecurity package is crucial for protecting online privacy and security. It should cover all devices and include antivirus, anti-ransomware, mobile security, password management, VPN, and parental controls.
Biometric technology offers robust security solutions despite inherent risks. These systems are convenient and difficult to duplicate. As they continue to evolve, the challenge lies in maximizing their benefits while minimizing risks.
FAQ’s
What is Facial Recognition?
Facial recognition is a method of identifying or verifying an individual’s identity using their face. This technology can analyze faces in photos, videos, or in real-time, and it falls under the category of biometric security along with voice recognition, fingerprint recognition, and iris recognition.
How does facial recognition work?
Facial recognition software compares two images of a person’s face – one recent and the other stored in a database. Algorithms attempt to match these images to determine the person’s identity. The process involves face detection, face analysis, converting the image to data, and finding a match in a database.
What are the applications of facial recognition?
Facial recognition technology is used for various purposes, including unlocking smartphones, law enforcement, airport security, finding missing persons, reducing retail crime, improving retail experiences, online banking, marketing, healthcare, tracking attendance, recognizing drivers, and monitoring gambling addictions.
What are the advantages of facial recognition?
Facial recognition offers increased security by identifying criminals and protecting personal devices. It helps in reducing crime by tracking down burglars and thieves. The technology also removes bias from stop and search procedures, enhances convenience by enabling face-based payments, ensures faster processing of identity verification, and integrates well with existing security systems.
What are the disadvantages of facial recognition?
Despite its benefits, facial recognition technology raises concerns about surveillance, potential errors leading to false identifications, breaches of privacy, and the need for massive data storage. There are worries about mass surveillance, privacy infringements, and the possibility of errors implicating innocent individuals.
How can individuals protect themselves from facial recognition security risks?
To mitigate risks associated with facial recognition technology, individuals should prioritize cybersecurity measures. This includes implementing comprehensive security packages covering all devices, using antivirus and anti-ransomware software, practicing good password management, employing mobile security measures, utilizing VPNs for online privacy, and enabling parental controls where necessary.
What are the future prospects of facial recognition technology?
Facial recognition technology is expected to continue evolving, offering even more advanced security solutions. However, the challenge lies in maximizing its benefits while minimizing risks, particularly concerning privacy and data security. As regulations evolve and technology advances, the future of facial recognition will likely involve striking a balance between security and privacy concerns.
Conclusion
Facial recognition technology presents both opportunities and challenges. While it enhances security and convenience, concerns about privacy, surveillance, and potential misuse loom large. Balancing these aspects requires robust cybersecurity measures, clear regulations, and ethical considerations. By prioritizing security and privacy while embracing innovation, we can navigate a future where facial recognition serves society responsibly.
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