Facial recognition has a long history dating back to the 1800s. To track down criminals, such as infamous bandits Jesse Woodson James and Billy the Kid, law enforcement would place “Wanted Alive or Dead” posters advertising bounties and soliciting public cooperation to help locate and even apprehend the alleged criminals. In addition to the bounty, these posters would include a photo and brief description of the crime, which would then be circulated to law enforcement agencies around the country and displayed in every US Post Office to speed up apprehension.

Facial recognition

Advancements in artificial intelligence and biometric technology have led to the widespread use of computerised facial recognition

Today, technology such as social media, television and other more specialised communication networks play a more influential role in the recognition process. Advancements in artificial intelligence and biometric technology, including the development of Machine Learning capabilities, have led to increased accuracy, accessibility and the widespread use of computerised facial recognition. The significance of this means that facial recognition can occur on an even larger scale and in more challenging environments.

This article will explore key milestones and technological advances that have resulted in the modern incarnation of facial recognition, before discussing the capabilities of cutting-edge “one-to-many” technology which is increasingly being used by counter-terror defence, police and security forces around the world.

Technology inception and developments

The technology was able to match 40 faces an hour, which was considered very impressive at the time

The 1960s marked the start of computerised facial recognition, when Woodrow Wilson (Woody) Bledsoe developed a way to classify faces using gridlines. Bledsoe’s facial recognition still required a large amount of human involvement because a person had to extract the co-ordinates of the face’s features from a photograph and enter this information into a computer. The technology was able to match 40 faces an hour (each face took approximately 90 seconds to be matched) which was considered very impressive at the time.

By the end of the 1960s, facial recognition had seen further development at the Stanford Research Institute where the technology proved to outperform humans in terms of accuracy of recognition (humans are notoriously bad at recognising people they don’t know). By the end of the century, the leading player in the field was a solution that came out of the University of Bochum in Germany – and the accuracy of this technology was such that it was even sold on to bank and airport customers.

From this stage on, the facial recognition market began to blossom, with error rates of automatic facial recognition systems decreasing by a factor of 272 from 1993 to 2010 according to US Government-sponsored evaluations.

The safety and security market requires near instant feedback on who a person matched against a watchlist is
The aim for facial technology is to achieve successful and accurate recognition on commonly available hardware like live CCTV feeds and standard computing hardware

Modern usage of facial recognition

Fast-forward to the modern day and facial recognition has become a familiar technology when using applications such as the iPhone X’s Face ID capability or MasterCard Identity Check, passport e-gates at airports and other security and access control points. These solutions implement a consensual form of identity verification, as the user has a vested interest in being identified.

This is a “one-to-one” facial recognition event, one person in front of the camera being compared to one identity either on a passport or the app. In these scenarios, the hardware is specifically developed for the application at hand, therefore technically much easier to accomplish.

Facial recognition can now be used in a variety of governmental and commercial environments The safety and security world brings a much more complex problem to solve – how to pick out a face in a moving and changing environment and compare it to several faces of interest. “One-to-many” facial recognition is a much harder problem to solve.

It’s even more challenging when the aim is to achieve successful and accurate recognition on commonly available hardware like live CCTV feeds and standard computing hardware. And unlike in the 1960’s where identifying a face every 90 seconds was acceptable; the safety and security market requires near instant feedback on who a person matched against a watchlist is.

Security and safety applications

The idea behind all facial recognition technologies is broadly the same: you start with an image of a person’s face (ideally a high quality one, although machine learning means that to a point we can now even use video without reducing accuracy). A fully front facing image is best, think a passport photo, but machine learning and new software has made this more flexible.

An algorithm converts this image into a numeric template, which cannot be converted back to an image and so represents a secure one way system. Every numeric template is different, even if it started out as an image of the same person, although templates from the same person are more similar than templates from different people.

The accuracy of facial recognition continues to increase alongside deployments in more challenging and complex environments What happens next sounds simple although the technology is extremely complex: templates of people’s faces are taken in real time and compared to those in the database. The technology identifies individuals by matching the numeric template of their face with all the templates saved in a database in a matter of seconds or milliseconds. To put this into perspective, imagine you are at the turnstiles of a busy train station looking for a person on the run.

Today’s facial recognition technology would be able to identify that person should they pass in view of a CCTV camera, as well as notify the police of any additional persons of interest, whether they are a known terrorist or missing vulnerable person on an entirely separate watch list.

Because of technical progression, facial recognition can now be used in a variety of governmental and commercial environments, from identifying barred hooligans attempting entry at a football stadium or helping self-excluded gamblers at casino to overcome addiction.

Real-time assessments

The latest evolution of facial recognition pits the technology against an even more challenging application – directly matching individuals from body worn cameras for real time recognition for police officers on the beat. This capability equips first responders with the ability to detect a person from a photo and verify their identity with assurance.

The broader implication for this means that every interaction, such as stop and search or arrest, can be supported by real-time facial recognition which will see cases of mistaken identity driven down on the streets. First responders can now for the first time be deployed and furnished with the ability to identify wider groups of people of interest with a degree of accuracy that previously relied only on the fallible human memory.

As the accuracy of the technology continues to increase alongside deployments in more challenging and complex environments, its ability to support government initiatives and law enforcement means the debate about the lawful and appropriate use of facial recognition must be addressed. Facial recognition should not be everywhere looking for everyone, but when used properly it has the potential to improve public safety and we should make the most of its potential.

Download PDF version

Author profile

In case you missed it

Artificial intelligence: why you should enable deep learning and video analytics
Artificial intelligence: why you should enable deep learning and video analytics

Constantly optimising deep learning algorithms yields better video analytics performance, even in complex applications such as facial recognition or in scenarios with variable lighting, angles, postures, expressions, accessories, resolution, etc. Deep learning, a form of artificial intelligence (AI), holds the potential to enable video analytics to deliver on long-promised, but not often delivered performance. Our AI series continues here with part 2. Adapting existing hardware Today, low-cost system-on-chip (SoC) camera components enable deep neural network (DNN) processing for the next generation of intelligent cameras, thus expanding the availability of AI processing to a broader market. AI software can even add learning capabilities by adapting existing hardware to AI applications AI software can even add learning capabilities by adapting existing hardware to AI applications. Today’s smartphones include cameras, gyroscopes and accelerometers to provide sufficient data to drive AI applications. Software can adapt existing hardware to transform them into AI devices capable of continuous learning in the field. Inside a video camera, real-time deep learning processing can be used to detect discarded objects, issue loitering alarms and detect people or objects entering a pre-defined field. Data capture form to appear here! Detect anomalous data Additional capabilities are applicable to demanding environments and mission-critical applications, such as the perimeter protection of airports, critical infrastructures and government buildings, border patrol, ship-tracking and traffic-monitoring (e.g. wrong-way detection, traffic-counts and monitoring roadsides for parked cars: all vital video security solutions). IoT is transforming the lowly security camera from a device that simply captures images, into an intelligent sensor that plays an integral role in gathering the kind of vital business data that can be used to improve commercial operations in areas beyond security. For example, cities are transitioning into smart cities. Deep learning enables systems to search surveillance footage, to detect anomalous data, and to shift surveillance from post-incident response to providing alerts during, or even before, an event. The ability of deep learning for video analytics is much more sophisticated and accurate Make critical decisions Deep learning can eliminate previous video analytics limitations such as dependence on a scene’s background. Deep learning is also more adept than humans at discerning subtle changes in an image. The ability of deep learning for video analytics is much more sophisticated – and accurate – than the programmed approaches previously employed to identify targets. AI is a timely solution in an age when there is more video surveillance than ever. There are too many cameras and too much recorded video for security operators to keep pace with. On top of that, people have short attention spans. AI is a technology that doesn’t get bored and can analyse more video data than humans. Systems are designed to bring the most important events and insight to users’ attention, freeing them to do what they do best: make critical decisions. Multiple camera streams AI can reduce information overload to enable humans to work with the data more efficiently The video benefits reflect the larger goal of AI to amplify human skills. AI can reduce information overload to enable humans to work with the data more efficiently. Another benefit is faster search, and new systems make searching video as easy as searching the internet. AI enables specific people or cameras to be located quickly across all the cameras at a site. Searching can be directed by a reference images or by physical descriptors such as gender or clothing colour. Consider a scenario of a child missing from a crowded shopping mall: Every second can seem like hours, and artificial intelligence and neural networks can enable a rapid search among multiple camera streams using only one photo of the child. The photo does not have to be a full-frontal passport-type photos; it could be a selfie from a party as long as the face is there. Intrusion detection scenario AI can find her and match her face from among hundreds of thousands of faces captured from video, in nearly real time. AI can also continuously analyse video streams from the surveillance cameras in its network, distinguishing human faces from non-human objects such as statues and animals. Privacy concerns are minimal as there is no ID or personal information on the photo, and the image can be erased after use. And there is no database of stored images.    In a perimeter security/intrusion detection scenario, an AI-driven video system can avoid false alarms by easily distinguishing different types of people and objects, e.g., in a region set up to detect people, a car driving by, a cat walking by, or a person’s shadow will not trigger the alarm. Part three coming soon. If you missed part one, see it here.

3 key security tips for public event planners
3 key security tips for public event planners

Public spaces in cities and suburbs are important places for community development and promoting outdoor recreation. These areas may include main streets, parks, promenades, band shells and fields. Such locations are often utilised by public event planners for community activities, including summer festivals, wintertime ice skating rink installations, music concerts and art fairs. As the year draws to a close, holiday and Christmas markets as well as major New Year’s Eve events, present cities with constant public event security needs. The public nature of these events increases risks of incidents with high-speed vehicles that put attendees in danger. Fortunately, there are three ways for public space managers to prevent casualty-causing collisions and further promote the use of local public areas. Developing an effective action plan    When strategising how to react to an alert, think about what time of the year and time of day the event is occurring It is important to have a plan developed before an incident or accident occurs. Warning systems, utilising doppler radar and digital loop technologies, alert guards to abnormal vehicle velocity changes in the surrounding area. Managers of public areas should organise a meeting with public safety authorities and local agencies to discuss what must immediately occur when a high-speed vehicle is approaching a public event. When strategising how to react to an alert, think about what time of the year and time of day the event is occurring. Having such a reaction plan in place combines technology and strategic planning to ensure everyone is on the same page to effectively target a threat and promote overall event safety. Securing public areas  Ideally, there will be no need to implement a well-conceived action plan. After all, taking preventive measures to secure public areas where events take place is important to keep people safe from accidental vehicle collisions and intentional attacks. Protect attendees by clearly separating pedestrian and vehicle locations using security devices such as – Barricades Portable barriers Bollards Install guard booths  Avoid the risk of vandalism and theft, making sure people are safe when walking back to the cars at night by keeping parking areas illuminated with flood lights. Install guard booths with employees who monitor activity in the parking area and who are prepared to react if an alert is triggered. Furthermore, prevent accidental collisions by clearly marking the parking area with informative warning signs and using barricades to direct traffic. These three tips can be used by public area managers to promote security at the next community event. Additionally, the technologies used to secure an event can also be used as infrastructure for year-round security. Installing gates that shut when the public space is closed or using aesthetically pleasing bollards are steps any public area manager can take to promote community safety.

Choosing your security entrance installation in line with your company culture
Choosing your security entrance installation in line with your company culture

The extensive analysis and discussion preceding any decision to implement a new physical security solution – whether it’s hardware, software or a combination of both – often focuses on technology, ROI and effectiveness. When it comes to deciding what type of security entrances to install at your facility, you will almost certainly also consider the aesthetics of the product, along with throughput and, if you’re smart, you’ll also look into service concerns. Each of these factors has its important place within the evaluation process, and none should be overlooked as they all have a significant effect on how well your entrances will perform once they are installed. Culture influences door solution decisions How significant will the change from current entrances to security entrances be for employees? Still, one additional factor actually trumps everything: if you have not considered your organisation’s culture in choosing a security entrance, you may be missing the most important piece of the puzzle. Culture is a part of every other decision factor when selecting an entry solution. Before you make a decision about what type of entrance to deploy, you need to consider and understand the values, environment and personality of your organisation and personnel. For example, how significant will the change from current entrances to security entrances be for employees? If people are accustomed to simply walking through a standard swinging door with no access control, this will be a culture change. Beyond this, whether you are considering a type of turnstile, a security revolving door or possibly a mantrap portal, simply walking through it will be a significant change as well. Training employees on door security You’ll want to know whether employees have ever used security entrances before. If these types of entrances are in place in another part of the facility, or in a facility they’ve worked in at an earlier time, the adjustment will not be as great as if they’ve never used them at all. Consider, too, how your personnel typically react to changes like this in the organisation or at your facility. They may be quite adaptable, in which case there will be less work to do in advance to prepare them. However, the opposite may also be true, which will require you to take meaningful steps in order to achieve buy-in and train employees to properly use the new entrances. With the increased importance of workplace security, discussing new entrances with  workforces will help maintain a safer environment Communicate through the decision-making process All of this will need to be communicated to your staff, of course. There are a number of ways to disseminate information without it appearing to come down as a dictate. Your personnel are a community, so news about changes should be shared rather than simply decreed. As part of this process, you’ll need to give some thought to the level of involvement you want for your staff in the decision-making process. Finally, do not overlook the special needs among your personnel population. You undoubtedly have older individuals on staff, as well as disabled persons and others who bring service animals to the office. Entrances need to be accessible to all, and you never want to be in the position of having a gap in accessibility pointed out to you by the individual who has been adversely affected. New security entrance installation By communicating early and often with your personnel, you can alleviate a great deal of the anxiety Once you have made the decision about which security entrances to install, training your personnel on how to use the new security entrances – both before and after the installation – will help to smooth the transition. Because workplace security is such a big issue right now, it makes sense to discuss the new entrances in the context of helping to maintain a safer environment. They will prevent violent individuals from entering, decrease theft, and most of all, promote greater peace of mind during the workday. If you can help them take control of their own safety in a responsible way, you have achieved much more than just a compliant workforce. By communicating early and often with your personnel, you can alleviate a great deal of the anxiety and concern that surrounds a significant change in the work environment. Schedule group meetings Consider your employees; what type of communications do they respond best to? A few suggestions to educate staff on the benefits of the new entrances include: Typically, you would communicate a general message 2-3 months in advance and then provide more specific information (for example, impacts to fire egress, using certain entrances during construction) in a follow up message closer to the installation date. Schedule group meetings to: announce the rationale for increased security, share statistics on crime, review the new security changes that are coming, show drawings/photos of the new doors/turnstiles, and show the orientation videos available from the manufacturer. These meetings are an excellent way to work through user questions and directly address any concerns. Once the installation of a new security system is complete, it is a good idea to have an "ambassador" on board to help employees use these new systems Ensure you monitor public areas If you are implementing a lot of new changes, such as a new access control system, new guard service and security entrances, you might consider hosting a ‘security fair’ on a given day and have the selected vendors come for a day with tabletop displays to meet employees and answer questions during their lunch. This could be a great way to break the ice in a large organisation. Make user orientation videos (provided by the manufacturer) available in several ways, for example: Intranet Site Monitors in public areas—lounges, cafeteria, hallways, etc. Send to all staff as email attachments Immediately after installation, once the doors or turnstiles are operational but before they are put into service, train ‘ambassadors’ on how to use the door/turnstile. Have these people monitor and assist employees during peak traffic times. What is the ultimate success of the installation? By communicating clearly and openly with your population you can greatly facilitate adoption and satisfaction If you have thousands of employees, consider dividing them into groups and introduce the new entrance to one group at a time (Group A on Monday, Group B on Tuesday, etc.) to allow a little extra orientation time. Place user education ‘quick steps’ posters next to the door/turnstiles for a few weeks to help employees remember the basic steps and guidelines, e.g., ‘stand in front of the turnstile, swipe badge, wait for green light, proceed.’ Ask your manufacturer to provide these or artwork. While there are always going to be people who are resistant to change, by communicating clearly and openly with your population you can greatly facilitate adoption and satisfaction. Your responsiveness to any issues and complaints that arise during and after the implementation is equally fundamental to the ultimate success of the installation.