Don’t Take Facial Recognition at Face Value: Various Uses & Applications of Face Recognition Across Different Industries
Part II of the series: Should Facial Recognition Technologies be Banned? We take a look at how different verticals are applying facial recognition technologies in their respective segments.
This article is the second in a three-part series that deal with the hot-button topic pertaining to calls for greater regulation and the resulting conversations and government scrutiny on facial recognition software. In the previous article, we took a look at the history of how facial recognition came to be, to illustrate the significant and rapid strides that the technology segment has taken. In this article, we will be looking at the technical capabilities of facial recognition technologies today, and how they are applied in various industries, as real-world solutions.
Facial recognition technologies can do more than just identify people today
From business solutions, commercial solutions and even solutions for the home—we take a look at how facial recognition is improving the way different industries work today—and where applicable, the exciting opportunities it presents for the future.
Beyond just unlocking phones or laptops, the biometric software behind facial recognition applications can accurately identify faces today, better than other people can (as we’ve gone through in our first article).
While this makes the technology an obvious choice for security and identification purposes, it can also be used creatively and repurposed to serve different industries.
While some of these examples are still in active development today, there are also many applications we will show that are already proving to be an integral part within a segment, and is disrupting and changing the way people live, work and play, today.
The various industry segments using and applying facial recognition technologies
1. Security companies are using facial recognition to secure their premises.
The fact that machines can today accurately recognize individuals, presents a slew of opportunities for the security sector, chief among them the ability to identify unauthorized access to locations where non-authorized people shouldn’t be.
It’s a well-known fact that IP cameras today can be equipped with facial recognition software, to enable complex access control of premises, with enabling of individual whitelists and blacklists for specific locations, enabling perimeter and asset monitoring, on top of threat and intrusion detection.
Security companies also regularly equip employees with body cameras, to enable video capture and recording during sensitive interactions and potential altercations when deploying security personnel to handle security intrusions. This is especially useful if security forces are engaging or handling intrusions in an area that may not be covered by fixed CCTV cameras.
In fact, many of the different applications of facial recognition technologies we will go through in the later points, are centered around security enhancements in application to a specific industry segment’s needs.
2. Immigration checkpoints use facial recognition to enforce smarter border control.
You’ve likely to have noticed and even enjoyed unmanned, automated immigration clearance gates. What you probably didn’t notice is the facial recognition technologies at work that protect our borders and keep borders secure in a variety of ways.
Chief among them is an ability to recognize and thwart border crossings from known criminals and persons of interests, through facial recognition. Border controls today, sync with information database such as INTERPOL’s ‘Facial Identification’ method, to identify individuals against an accuracy scale. Processing facial information over the cloud also gives ample opportunities to run predictive algorithms over the footage to factor in things beyond just typical quality-of-image-enhancements, but factors like aging, plastic surgery, cosmetics and even the effects of narcotics.
3. Fleet management companies can use face recognition to secure their vehicles.
In fleet management, facial recognition could be deployed to send alerts to unauthorized individuals trying to gain access to vehicles, preventing theft. The potential for this technology to work in conjunction with the advent of self-driving cars is exciting. What if cars could—in an effort to prevent theft of the vehicle, or it’s contents—react to robbery attempts?
While current solutions designed to draw attention to the vehicle by the means of loud sounds could work, it doesn’t always foil a determined criminal. In the future, vehicles could just, drive away, removing them from a criminal situation, without human supervision.
With the fact that inattention—largely through smartphone usage—is the leading cause of accidents after alcohol and speeding, facial recognition technologies could be programmed to detect when a driver’s eyes are not on the road. Likewise, it can be trained to detect eyes that give away an inebriated or tired driver, increasing the safety of vehicles in fleets.
Managers can also use collated information from various riders, to inform them of trends and patterns with analytics, which could become a basis of a rider safety program which can be rolled out to enhance driver safety standards across fleets.
4. Ride-sharing companies can use facial recognition to ensure the right passengers are picked up by the right drivers.
In a similar vein to the fleet management solutions presented above, passengers in the ride-sharing industry can also benefit from facial recognition. In the case of the sharing economy, facial recognition presents an added layer of verification—and security—to rides.
Grab, a ride-hailing company based in Southeast Asia that acquired Uber’s Southeast Asian stake—and resulted in Grab exiting the market, today partners with Microsoft to incorporate facial recognition technologies to accurately identify the right drivers and passengers for each ride. This adds another layer of security, providing ease of mind to commuters in a market that isn’t always known for passenger safety.
Not too far away in India, where Uber still operates, drivers are required to scan their face on their mobile device, to verify their identity—and the corresponding driver and safety credentials. This information is relayed to their passengers to once again, give them ease of mind.
In the future, cars could come with native face-scanning technologies, that can enable the added security benefits without the need for an additional device. It can go as far as recognizing faces, and only unlock vehicles and allow passengers to board if they were the ones who booked the ride—presenting the best type of security there is. Security, that seamlessly integrates with user behaviors, so users won’t even notice.
5. IoT benefits from facial recognition by allowing enhanced security measures and automatic access control at home.
Once again, a security-driven application of facial recognition finds its way in the IoT sphere. In homes, the key use of facial recognition is on intrusion systems, that detects if someone enters a home when an intrusion alarm is left armed.
Progress within this sector could be in the form of enhanced capabilities of existing intrusion devices, to extend into access control ones. In the future, doors could unlock when homeowners reach their front door, negating the need for traditional door locks and fumbling with keys, or relying on mobile devices to manually unlock “smart” lock solutions of today.
In extension, such technologies could theoretically work in parallel with existing facial recognition technologies baked into social networks like Facebook (which are, unfortunately, not something you can do today as developers have no access to the facial recognition APIs of the platform). Hypothetically, Facebook events could plug into IoT devices to enable automatic access to invited visitors who have RSVPed prior.
Another possibility is to allow access to homes and premises to known contractors when the homeowner isn’t around. Truly, the possibilities that facial recognition could unlock (pun intended) for homes is truly immense.
6. Law Enforcement can use facial recognition technologies as one part of AI-driven surveillance systems.
In China, the much-discussed social credit system being tested in cities like Rongcheng, a city 500 miles from Beijing that served as a test-bed for the deployment of city-wide facial recognition technologies has already proven itself. A Chinese suspect attending a concert of 60,000 people was arrested after being correctly identified and located by China’s network of 170 million CCTV cameras.
In America, facial recognition is used by law enforcement agents too. Police departments across America have purchased and integrated face recognition into their processes. Estimates on American law-enforcement procurement go up to US$375 million by 2025, up from US$136.9 million today. This presents an almost-threefold-growth, showcasing the utility of the technology for law enforcement agencies.
Facial recognition has already proven effective in identifying criminals in America. In Colorado, investigators correctly identified suspects in a shooting and road-rage incident; in Pennsylvania, a rapist was rightfully identified; in South Carolina, robbery suspects nabbed.
One key player supplying technologies that power facial recognition is Amazon. It sells facial recognition technologies to a wide range of enforcement agencies. While some aspects of the technology can be said to still be in a nascent stage—Amazon falsely matched 28 members of the US Congress with criminal mugshots—it presents exciting frontiers to enhance law enforcement work.
For example, one of the bleeding edge applications facial recognition research based on Eigenfaces (which we discussed in our first article), is “face hallucination“. One application of this is the identification of masked suspects through an algorithmic reconstruction of a full face, even when only periocular regions of a face is visible. Facial recognition methodologies are applied to compare the “hallucinated faces” to images of actual faces to find ones with a strong correlation.
7. Retailers can use facial recognition to customize offline offerings and to theoretically map online purchasing habits with their online ones.
The retail industry recognizes that facial recognition is the next step in their continuous pursuit to provide personalization for shoppers.
Facial recognition could allow retailers to capture what shoppers are looking at in physical shops, turning what was long-known as “offline” shopping habits, into online ones as well. This essentially means greater insights and analytics into the purchasing habits of their customers.
Amazon opened its first Amazon Go store in the US in 2018, allowing users to walk in, get what they need and walk out. No check-out required. At least not in the traditional scan-and-pay sense. With a mix of technologies powering such stores, including facial recognition, Amazon can identify users and charge them for the items they walk out with without the need for cumbersome lines. The technology presents an exciting future where shoppers need not queue, just taking the things they need—and going. With Amazon slated to open more stores in the US, and even the UK in 2019, this future seems to be close.
Amazon too is driven by the possibilities of mapping offline customer behaviors with online ones. In today’s age of data economics, such information is invaluable to maximizing user spending with constantly tailored offers and marketing messages based on each user’s actual shopping habits.
Physical retailers can also glean more information about the state of mind of their different shoppers by literally, the look on their faces. Facial recognition technologies can identify a whole range of emotions—happy, sad, anxious, angry—allowing actionable reports to on-ground retail operators.
Facial recognition technologies have become somewhat of a commodity, used by many industries
The 7 examples we ran through are by no means an exhaustive list for the application of facial recognition. With that, we hope you have gained greater insight into how different verticals are using the technology to improve the ways in which they work.
With ongoing calls for regulations and even recent bans in California on facial recognition technology, we have to ask, do the cons outweigh the benefits of facial recognition?
We’ll discuss that in detail in our third and final article in the series, and give our two cents, as a company that supplies technologies with image and scene recognition capabilities. Stay tuned!
