Various segments of the – quite diverse – facial recognition market are poised to grow and in some types of applications and use cases, facial recognition might become a reality faster than you expect.
3D facial recognition software overcomes the drawbacks of 2D facial recognition and can work in low light or completely dark areas
For the technology industry, the growing facial recognition market overall is a commercial blessing, pure and simple. Although the focus in the more pervasive applications is often on the machine learning technologies that enable the matching of images from cameras with images in databases, complex facial recognition systems need and are enabled by far more technologies.
There is the hardware, the infrastructure to capture and interpret the data with facial recognition analysis tied to edge computing, the connectivity aspect, the software, the services, the list goes on. In fact, facial recognition and the deployment of high-density networks of AI-supported security cameras to monitor literally anything is most probably the first major area where 5G cellular IoT (yes, the Internet of Things plays a role too) can have a significant impact: homeland security.
If you start looking on an application level it even goes much further since facial recognition is growing fast in specific areas that aren’t about government, defense and security surveillance.
What You Will Learn
Facial recognition in consumer applications
Many might immediately think about things like airports and cross-border checks, surveillance and similar applications when hearing about facial recognition but facial recognition applications are also tested in retail facilities (not just for security, also for self-service checkout and far more), used by social networks, tried for marketing purposes, tested/used in digital healthcare (patient screening) and some say it’s key for the future of mobile banking and mobile commerce (secure mobile payments and authentication).
The majority of smartphone facial recognition will be software-based, with over 1.3 billion devices having that capability by 2024
According to Juniper Research, for instance, facial recognition hardware, such as Face ID on recent iPhones, will be the fastest growing form of smartphone biometric hardware (from an estimated 96 million smartphones in 2019 to over 800 million in 2024).
While facial recognition hardware will grow over 50 percent each year during the forecast period, these software solutions will be on 1.3 billion smartphones per Juniper Research, enabled by advances in artificial intelligence, with companies like iProov and Mastercard offering facial recognition authentication that is strong enough for payment and other high-end authentication tasks.
Obviously you can imagine other scenarios where authentication is needed for payments or other services (e.g. access) in consumer-oriented applications. In an article on technologies in the hotel industry we, for instance, mentioned how one of the panelists saw facial recognition as an opportunity for payments and room access, taking into account data privacy issues. Facial recognition is already used for building access on other areas than the hotel industry too of course.
Facial recognition software and services
Another market that’s growing is that of facial recognition software tools and solutions. However, it’s clear that growth won’t be the same everywhere in the world.
As you know, facial recognition, homeland security and the usage of facial recognition systems for the identification and verification of ‘criminals’, forensic video investigations, cross-border monitoring and law enforcement are the subject of fierce debates.
The media attention for the Clearview AI story where we have an apparently huge AI image database that was built in very dubious ways and is used on a quite large scale by law enforcement in the US is just one recent example. Mass surveillance concerns regarding the usage of face recognition in some parts of the world are food for other debates. And then there are all the issues regarding bias and abuse regarding facial recognition algorithms.
Facial recognition becomes more accurate
Despite calls in the EU to ban facial recognition applications for some time (there are certainly facial recognition systems in place that adhere to the GDPR’s personal data protection rules) and the actual banning of it in some other regions, facial recognition isn’t going away and continues to be developed, becoming more and more accurate.
The advent of new technologies, such as high-definition Closed Circuit Television (CCTV) and high-resolution 3D facial recognition technologies, along with iris recognition and emotion detection, has enhanced the facial recognition market
More powerful special micro-controllers and processors, better images with better cameras and on-chip processing and edge computing for more intelligence in and close to the cameras, 3D facial recognition and ever more accurate face recognition algorithms thanks to neural network algorithms are just some of the evolutions from the past few years.
The main reasons why facial recognition isn’t going to go anywhere is because:
- the fact that there are very different attitudes across the globe,
- demand is high (and not just from governments and law enforcement, as said there are applications in marketing, retail, the protection of critical facilities, etc.) and
- although there are more accurate biometric measurements it’s far easier to use – at scale – and offers far more opportunities for those using it.
Concerning the latter: the usage of fingerprints for instance, another topic that is debated in some countries in recent years, requires an action from the individual; facial recognition strictly speaking doesn’t, at least in public spaces and where no one tells you it’s used.
The debates on facial recognition applications aren’t new but the calls to ban them in mainly public circumstances for a while are louder than ever with the Clearview AI story making waves.
The question to consider, however, is not about facial recognition that could be used for the better here and there as well. It’s about all the technologies that enable surveillance at scale and how we’re building a digital surveillance environment that inevitably is and will continue to be misused by big tech companies and governments alike. It’s a human and social issue and we’ll see where it ends.
The market of facial recognition software systems and services
Time for a look at the facial recognition systems market and its drivers. Per a report ‘the rising need for surveillance has become one of the major factors to drive the facial recognition market’. Where that rising need comes from and is fueled most or is highest is up to your judgment.
According to the MarketsandMarkets report the facial recognition technology market will reach $7 Billion by 2024. For the period 2019 ($3.2 Billion) – 2024 that means a compound annual growth rate of 16.6 percent. To give an idea of the ‘importance’ of this market, at least according to the MarketsandMarkets data: worldwide spending on the Internet of Things is expected to surpass the $1 trillion mark in 2022.
Increasing need of facial recognition-enabled biometrics solutions for identity management, border management, and homeland and military security management have fueled government organizations to largely implement facial recognition technologies
The market seems small. But predicting its size and evolution seems like a very challenging task, given all the debates and uncertainties ahead. As said, the report only looks at facial recognition software tools and related services. Or in other words: the scope of the approach of the research obviously doesn’t show the full ‘market value’ beyond solutions and services and as mentioned, there is a huge market for facial recognition infrastructure.
The software tools concern 2D facial recognition, 3D facial recognition and facial analytics. As you can imagine, 3D facial recognition technology is ‘better’ than 2D facial recognition for several ‘use cases’ where 2D doesn’t do too well. It is also the largest segment from a market size perspective with 3D facial recognition mainly being used in cross-border monitoring, document verification, and identity management.
The main companies in the areas the report covers are NEC (Japan), Aware (US), Gemalto (Netherlands, now part of Thales), Ayonix Face Technologies (Japan), Cognitec Systems GmbH (Germany), NVISO SA (Switzerland), Daon (US), StereoVision Imaging (US), Techno Brain (Kenya), Neurotechnology (Lithuania), Innovatrics (Slovakia), id3 Technologies (France), IDEMIA (France), Animetrics (US), and MEGVII (China).
The countries and segments where facial recognition software is most used
Given all the existing initiatives, it’s not a surprise that the Asia Pacific region will account for the highest growth during the forecast period, among others driven by government investments in security and surveillance infrastructure.
The main APAC activity is in China, Japan, Singapore and, increasingly, India. Another factor contributing to the growth is increased public awareness, an important one to watch indeed.
Integration of new facial recognition technologies with the existing legacy system is limiting the growth of facial recognition solutions in the market
In other regions, the US, Canada and the UK have been investing quite a bit in facial recognition and continue to do so. The government and defense vertical has been the main contributor to the market and also continues to be one of the fastest growing sectors.
Facial recognition solution adoption is also increasing in government-owned large-scale programs, such as smart cities and smart transportation per MarketsandMarkets. Yet, so far, ‘increasing need of facial recognition-enabled biometrics solutions for identity management, border management, and homeland and military security management have fueled government organizations to largely implement facial recognition technologies’ as you can read here.
Other verticals where quite a bit is happening include Banking, Financial Services and Insurance (BFSI), healthcare and retail and education. We gave a few examples of applications in the scope of some of these segments.