Facial recognition is one of the many applications of modern AI technology. It’s also one of the oldest – it’s been quite a while since the first facial recognition systems dropped on the market. Some initial designs were even trying to tackle the problem with conventional “rules based” programming.
With machine learning driving current approaches to face technologies, the accuracy and speed of facial detection and recognition algorithms are becoming very impressive. Judging by how much the tech behind facial recognition has advanced over the last five years alone, it’s exciting to think of the future potential that it holds.
But what is facial recognition actually being used for these days? As it turns out, quite a lot. Let’s have a look at some of the most popular use cases, the challenges the technology faces, and what the future might hold.
You’ve probably seen or even used this yourself already. Facial recognition is available as an option for unlocking some smartphones and tablets. While it’s not as convenient as fingerprint recognition for the user in most cases, it offers some clear advantages, like improved security. Combining the technology with an iris scanner and other advanced solutions can prevent tricks like using a picture of the user to fool the system. Some systems may also require the user to perform certain facial expressions in order to verify that they are a live human being.
That’s also the reason why the facial recognition tech is enjoying so much popularity in more advanced environments, like high-security facilities. It’s a much more convenient solution than remembering a keycode or carrying around a keycard, and it can often work without requiring any specific user action. One could just walk up to a secured door and be granted access as they approach. At the same time, this technology is far less prone to attacks involving stolen credentials, for obvious reasons.
Attendance monitoring is important in environments like schools and workplaces. This can be done for statistical purposes, or for ensuring that mandatory attendance rules are followed. Traditional methods have been slow and cumbersome and prone to error (for example, in cases of somebody arriving late). Facial recognition software has made it possible to streamline this aspect, ensuring that attendance is properly recorded without requiring any specific actions from neither attendants themselves, nor from teachers and other supervisors.
This can be taken one step further and combined with systems that record attendance statistics and run complex evaluations on them to identify patterns. This is already done in many places, like some universities, for the purpose of optimizing schedules and minimizing wasted resources. Facial recognition has proven to be of huge help in this area, and will likely continue to enjoy a lot of attention in the same circles in the near future. These solutions can be easily integrated into other setups, like remote learning, something which has become particularly important during the 2019-2021 period.
Large venues and events with high attendance are traditionally difficult to manage and oversee. A lot can go wrong, and the sheer manpower requirements can be significant. Or at least, that used to be the case. With the help of modern facial recognition solutions, the situation is becoming much easier to manage. Venues can now identify important guests in crowds and provide them with special directions to VIP areas and similar areas. This can even work out in large crowds, removing the need for uncomfortable sorting of guests via means like queue lines and similar obstructive elements.
Facial recognition software can also help organizers identify when there are issues that need immediate addressing, such as a part of the venue becoming overcrowded, or certain guests not receiving the attention they might expect. It’s little details like these that can add up very quickly through the use of modern facial recognition solutions, and part of what makes facial recognition such a valuable market right now.
This can play into safety considerations, not just guest satisfaction. That’s why there has been a lot of attention to this particular part of the field. A lot of work is being done on combining facial recognition software with systems that analyze the environment for potential health hazards, and notify people in a timely manner without causing panic. These are showing great promise already, and are likely going to be used very actively in the near future.
Various types of businesses tend to have recurring issues with keeping unwanted people out. This can not only cost time, money and manpower, but it’s also a critical part of ensuring smooth operation of the business. One unpleasant incident with a person who should not be there in the first place can drive many people away for good.
Retail stores and casinos are among the main users of these solutions. Loss prevention is already a huge market on the retail side, but there have been concerns about the effectiveness of current approaches, as well as the downsides they impose on business operations. Having people walk around a store looking out for potential thieves is both costly, and it can also leave a bad impression on customers. Facial recognition software can help ensure that nobody who’s been banned from entering the establishment enters in the first place. It can also help keep track of the activities of people on the premise. Combining this with other analytical systems can result in a very efficient deterrent system for unwanted visitors.
Casinos are not new to using modern facial recognition software solutions as part of their security. Casinos tend to be quite advanced in their overall security setups and are usually on the cutting edge of relevant solutions. It should be no surprise that they are among the main adopters of what this corner of the AI market has been producing.
While this has been a bit of a controversial topic, there’s no denying that facial recognition has a huge potential to improve the world of social media. Platforms like Facebook have already attempted some solutions of this type. One example was a feature that automatically tagged people it recognized in newly uploaded photos. However, that particular feature – and the way Facebook approached it – faced some backlash at the time of its unveiling.
But beyond that, facial recognition software can make it easy for people to find friends they haven’t yet connected with, sort and categorize their memories in more accessible ways, and generally get a better experience out of their use of popular social media platforms. This also applies to “live” versions of social media platforms, like Twitch streams.
The use of facial recognition in these areas is still being actively explored, and many challenges remain, not the least of which is ensuring user privacy while incorporating these types of technology. But there is no doubt that social media is going to be at the forefront of the technology and policies around facial recognition.
In order to grow sales and customer loyalty, retailers want to cater to their most valued customers and provide them with personalized attention.
With the evolution of AI, you can use face recognition to identify your high-value customers via video camera and provide them with “gold star” treatment as they enter your store or any physical space.
With AI and the help of video analytics, VIP alerts can be sent to service staff with specific information on customer preferences to hyper-personalize their visit or simply help VIPs “skip the line.”
AI can also be used to support targeted advertising programs for these high valued customers based on anticipated store visits. These programs would include emails and text promotions tailored to VIP interests to drive continued loyalty and up-selling and cross-selling opportunities.
Crime prevention is another field that’s being actively explored through the perspective of active use of modern facial recognition software. Facial recognition is only one part of the puzzle here. These systems often leverage other analytical solutions, like natural language processing (NLP), behavioral analysis, traffic data and more. By feeding all of this to a complex analytical engine, various patterns and connections can be identified which a human would never spot on their own.
And through this, certain types of crime can be prevented before anything bad has even happened. Of course, police are not allowed to overstep their boundaries and arrest suspects who have not actually done anything. But the information gathered from systems like these can allow them to keep a close eye on someone they know is likely to do something, and be alerted when they are making a dangerous move. This has already been deployed experimentally in some places. And while the technology is far from perfect – it requires human oversight all the time to prevent unfortunate errors – it’s a glimpse into what the future holds.
The finance sector is another field where we’ve been seeing more and more active use of facial recognition software. Some banks have integrated such solutions into their mobile banking systems, removing the need for passwords, PINs, TANs and other arguably outdated solutions. Some ATMs also employ facial recognition software as an added layer of security. This can be useful not just for verifying that the person making a withdrawal is the owner of the account, but to check for other people potentially manipulating them in the background.
And of course, the same is also true for physical interactions in banks themselves. Modern banks make heavy use of facial recognition for a large number of purposes, often a mix of most of what we described above. Special clients can be identified and addressed immediately upon entering an institution, known criminals can be monitored closely, and employees can navigate the premises without having to scan a keycard every few feet. All of these factors have relieved banks and other financial institutions of a large portion of the burden they normally carry in dealing with their customers.
Facial recognition is only the tip of the iceberg here anyway. Banks are known for their heavy use of modern solutions in artificial intelligence in general, and this should come as no surprise to anyone familiar with the sector. It’s a unique environment that combines the need for advanced, cutting edge security, with fast and accurate service. All of these are factors that make the introduction of AI systems ideal.
Traffic administrators have been able to tighten their grip on those who abuse their road privileges quite efficiently in recent years with the use of facial recognition software. Speed cameras can capture a picture of a driver’s face and submit it to a database for identification, allowing systems to figure out who was behind the wheel even in cases where the license plate was obstructed and no other easily identifiable details can be seen.
It’s not just about punishing violators though. Another popular example of the use of facial recognition software in traffic has been in toll booths and similar environments, where a driver’s face may be scanned as they approach, allowing them to pass through without any additional interruption or slowdowns. The use of these systems is also becoming popular in private environments, with people utilizing facial recognition to improve the security of their homes while also making things like driving the car in the garage slightly more convenient and straightforward.
Last but definitely not least, healthcare is another field where facial recognition solutions have been enjoying a lot of popularity. Some people don’t realize this yet, but facial recognition can be used for a lot more than simply telling if something is a face or not, and identifying one face from others. The technology also shows great potential for things like advanced health diagnosis. This applies both to physical conditions, as well as mental ones. Modern facial recognition systems in healthcare are being trained to identify certain conditions based on just how a person looks, requiring no further intervention from a healthcare specialist.
This can also allow healthcare specialists to provide a much more personalized approach to the treatment of their patients. A patient’s needs are already assessed on an individual level for most types of treatment. But when we throw some advanced analytics in the mix, the potential results are nothing short of amazing to think about. Doctors can know that a patient needs certain types of special attention before they’ve even said so themselves, and they can adjust their treatment approach adequately.
All of this is already amazing to think about. Facial recognition is all around us, and we sometimes don’t even realize when something is powered by this technology. Many industries have an active interest in seeing it evolve even further, which is why it’s very reasonable to expect to see a lot of progress in the coming years. As we mentioned above, progress is already happening at staggering rates – so the next five to ten years will be an exciting time for those following the development of those systems from a close perspective.
It’s also a great time to get involved for those who believe they have something to contribute. Facial recognition is already a broad enough field that it’s not just data scientists, statisticians and programmers that are being sought. It’s actually highly likely that we’re going to see the field expand even more in terms of its requirements for specialists in the near future.
