The State of Facial Recognition Software in 2019

  • Maxine Hunt
  • July 25, 2020
  • Comments Off on The State of Facial Recognition Software in 2019
  • General

Facial recognition (FR) is probably one of the most commonly accepted AI technologies in the category of image analysis software. People are used to things like Windows Hello and Apple Face ID. These are great examples of how FR is making our lives easier. Even pop culture is starting to take note of the tech, with stars like Taylor Swift using FR to identify unwanted concertgoers.


At the same time, the quality of FR technologies has been steadily improving, paving the way to its much broader adoption across the globe. According to the research by the National Institute of Standards and Technology, the accuracy of FR has improved by 20 times in less than a decade.

This report aims to shed some light on the broader state of FR technologies, their advances, and their much wider range of use cases, which some businesses and consumers might not be aware of. Additionally, we’ll take a look at some of the obstacles that FR tech has to overcome on its way to mass adoption.

Facial Recognition Software: Market Outlook

While people are getting more used to FR embedded in their devices, privacy advocates point out that it’s essential to maintain a proper balance between achieving convenience and being constantly monitored.

That’s why it’s tough to predict how the market will be shaped in the next decade. The possible regulatory updates and shifts in public perception might have a massive effect on FR as an industry. Right now, the outlook is pretty positive, but that may drastically change.

One of the biggest drivers of the adoption and development of facial recognition software is the interest from governments and governmental agencies. The U.S. Department of Defense is investing in the tech but meets a lot of opposition from the public and even from the employees of companies that supply the technologies. But the trend isn’t going to change, as the U.S. government is planning to invest even more in biometrics based on FR in the coming years.

Chinese FR startups are raising hundreds of millions of dollars in investments, including from government-backed funds. The country will remain the leader in this industry, given the ongoing investments and expansions. It will soon have over 500 million CCTV cameras, which is around one camera per 5 citizens. China also leads the way in FR patents, filing 10 times more patents than the U.S.

It’s undeniable that FR is here to stay, but will its development context prove to be ethical?

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Privacy and Security Concerns

You would worry if a stranger was walking next to you the whole day while simultaneously looking you in the eyes. Similar privacy concerns are associated with FR. Only this kind of intrusion raises a broader assortment of privacy and legality questions.

And these concerns are not baseless. In 2017, the UK police used FR to identify potential wrongdoers during the Champions League Finals, which led to over 2,000 people being wrongfully matched to actual criminals. In this particular instance, FR failed in 92% of the cases.

Amazon, one of the leaders in AI and FR, also gets its fair share of flak for its products, like in 2018, when its system confused over two dozen members of Congress with criminals. Some lawmakers even went as far as to call Amazon’s software racially biased. Sure, we might be inclined to insert a political joke here. However, it’s obvious that cases like these spark the general public’s concern about the future of FR.

Luckily, companies like ModiFace, recently purchased by L’Oreal, are already addressing possible privacy and bias concerns. They’re doing this by providing as diverse data to their facial recognition software as possible, with a curated database of 250,000 images that include people from most dominant ethnic groups. This way, when the system uses photos to learn how to recognize faces, it will be more trained to recognize racial nuances and better identify facial features.

Even schools are now experimenting with FR to monitor their students. For example, SAFR offers its FR software to K-12 schools for free. This naturally alarms privacy rights groups and concerned parents.

That’s why some of the biggest AI research organizations, like the AI Now Institute, are calling for regulations when it comes to FR tech. Even Microsoft’s leading legal executive, Brad Smith, recently pointed out that FR software needs to be regulated.

According to a prominent law firm, Drinker Biddle & Reath, companies adopting FR technologies have to be aware of the fact the regulations might soon catch up with the technology. And this might require considerable investment and restructuring of the current processes. A great example of such a regulatory shift is the GDPR: FTSE 350 businesses spent over a billion dollars just preparing for it.

Now, these circumstances should not dissuade any company from exploring the opportunities that come with FR—from improved security to better product personalization for customers. Let’s dive deeper into some of the use cases and industries that can benefit from FR in the nearest future.

Facial Recognition Software in Retail

While many people might still consider FR to be a novel concept, for the retail industry it’s becoming increasingly widespread to the point of becoming a mainstream technology in a couple of years19. That’s why the market for FR in retail is projected to be worth over $7.7 billion by 202220. Below are some of its most valuable and promising applications.

• Theft and Fraud Control

According to the National Retail Federation, the damages to the industry from theft by employees, shoplifters, and criminals amounted to almost $50 billion in 2017 (figures for 2018 haven’t yet been released). This also impacts product availability, further worsening customer experience for honest shoppers.

These figures put additional pressure on the bottom line, making retailers search for the most accessible and cost-effective solutions to this problem. This is where FR can truly shine.

For example, Fraud-IQ is a system that’s being deployed by some U.S. retailers to combat returns fraud, which accounts for 21% of all returns made without a receipt. The premise of such a solution is simple. The system recognizes the faces of people and determines whether they entered the store with the product that is being claimed as a return.

The same technology is being tested and implemented by retailers as a way to detect shoplifters before they commit a crime. But not all applications of FR in retail have such a negative connotation.

• Improving Customer Experience

Understanding in-store customer experience and preferences is the holy grail for retailers. Fighting for dominance and revenue against online retailers, like Amazon, is a tough game and so any advantage is crucial. That’s why retailers are exploring ways to use FR to improve their understanding of how shoppers feel during their visits. For example, 7-Eleven, an international chain of convenience stores, is using FR to analyze in-store behavioral patterns, which could be used to optimize stocks and create customer loyalty profiles.

Another great implementation of FR is KFC’s “smile-to-pay” system. Its widespread adoption is a testament to the fact that consumers are more than welcome to accept such tech: it first rolled out in 2017 as a pilot for a single location, but now it’s being implemented across 300 restaurants all over China.

Applications like these also solve a different problem, which is availability of human resources. For example, one of China’s biggest retailers,, is using FR to identify shoppers and charge their accounts as they leave their stores without any floor personnel and cashiers.

As these examples prove, FR can be extremely impactful on how retailers conduct their business and how shoppers behave. Examples from stores like the pioneering Amazon Go show that people are willing to give FR a chance. As long as the implementation is done in a transparent manner, shoppers accept the use of the tech. All for the sake of streamlining their shopping experiences.

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Facial Recognition in Travel and Hospitality

The travel and hospitality industry relies heavily on the quality of customer experience to generate revenue. On top of that, customer experience is mostly shaped my interactions, like during a check-in, which creates opportunities and use cases for facial recognition software. This innovation is also greatly facilitated by the advances in FR tech, which make it easier to set up and operationalize new FR-based systems.

• Authorization and Access Control

Augmented approaches to customer authorization in hotels and airports don’t always work since even mobile check-in becomes another friction point.

Facial recognition provides an opportunity to simplify customer authorization and streamline it even further. Marriott is rolling out its FR-powered check-in system at dozens of its properties. According to Marriott, this has the potential to shorten the check-in process by three times. Other hospitality businesses are also slowly rolling out similar systems, like the French Accor Hotels in one of its Brazilian properties.

Delta, one of the biggest US airlines, is also experimenting with FR for its international flights. This should improve the check-in experience and eliminate the already shrinking amount of paperwork required to get on a plane. Although the adoption rate still remains low, Delta is hoping to expand the impact by making FR available at more airports, such as Detroit Metropolitan Airport.

Federal authorities are also using facial recognition software to authorize passengers, as the U.S. Customs and Border Protection claims that these systems reach a 99% accuracy rate. The U.S. Customs and Border Protection has even caught an imposter with a fake ID with the help of facial recognition.

There is a growing list of such systems working around the world to improve the check-in and customs experience for passengers. For example, Malaysia, France, and UAE are already exploring or installing facial recognition systems at their airports. Beyond improving arrivals and departures of travelers and hotel guests, facial recognition can be used as a personalization technique:

  • Instead of carrying a key card or identifying yourself to the hotel staff, a guest can get access to facilities and services based on their profile through the hotel’s facial recognition system.
  • Hotels can match a guest’s face to the data stored in their database and suggest personalized offers based on the guest’s previous stays and available loyalty promotions.

Similar access control applications are being implemented in other adjacent industries that continually deal with large volumes of people. For example, products like Mexia One allow event organizers to abandon the legacy approach to ticketing and tagging by using facial data to grant access to their events.

It is, however, important to remember that 70% of consumers still prefer human interactions. Companies need to find the right balance between automating some of the above-mentioned functions and maintaining a human presence throughout the process.

Authorization and access control via facial recognition is soon to enjoy widespread adoption. Recent use cases in the travel and hospitality sector in 2019 Iflexion research.

Facial Recognition in Healthcare

Unlike previously covered industries, healthcare has a broader set of use cases for FR. However, it’s important to note that security and access control remain some of the most important ones, as hospitals represent sensitive environments, and safety is paramount to their effective operations.

• Better Patient Management

Managing secure and operationally-sound access to medical facilities is an important use case for FR. And while security concerns are at the top of the list, there are other uses for identifying patients and staff to achieve more cost-efficiency.

Duplicate records could cost hospitals $2 thousands per inpatient stay. As an example of an institution fighting this issue, Northwell Health is experimenting with FR as a way of eliminating duplicate records by tying patients’ photos to their EHR data.

• Improving Self-medication

Limiting unwanted access to medications is essential to many healthcare providers because of the liability and care quality risks. But that’s even more true for at-home medical devices, which dispense drugs according to the prescription and schedule. One maker of such products, AceAge, is incorporating FR into their devices to improve the safety of their customers. The medication is only dispensed when your face is analyzed and authorized to access the drugs.

At the same time, such tech could be used by pharmaceutical companies during trials to better control and survey drug adherence.

• Spearheading Novel Applications

Healthcare has always been the hotbed of innovation. And that’s why it’s not surprising that there are plenty of unique applications of FR in the industry.

For example, the Houston-based HOOBOX Robotics creates wheelchairs that can be controlled by FR. It could be stopped with a smile or launched with a raised brow.

Diagnostics is another potential field for FR. The National Human Genome Research Institute in the U.S. already has a system that can recognize rare genetic conditions just by analyzing a person’s facial features. In fact, there are already apps that doctors can install on their phones to assist them in identifying people who might have a genetic condition.

We can already see a combination of these technologies with other AI-powered tools and appliances designed to improve health monitoring. An example would be Lucent, a mirror that can scan your face and recognize possible genetic risks for you and your family members.