Fernande van Schelle

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 Today, technology such as social media, television and other more specialized 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 computerized facial recognition. The significance of this means that facial recognition can occur on an even larger scale and in more challenging environments. Advancements in artificial intelligence and biometric technology have led to the widespread use of computerised facial recognition 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 defense, police and security forces around the world. Technology Inception And Developments The 1960s marked the start of computerized 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. The technology was able to match 40 faces an hour, 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 recognizing 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 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.

Timely and important issues in the security marketplace dominated our list of most-clicked-upon articles in 2018. Looking back at the top articles of the year provides a decent summary of how our industry evolved this year, and even offers clues to where we’re headed in 2019. In the world of digital publishing, it’s easy to know what content resonates with the security market: Our readers tell us with their actions; i.e., where they click. Let’s look back at the Top 10 articles we posted in 2018 that generated the most page views. They are listed in order here with a brief excerpt. 1. U.S. President Signs Government Ban On Hikvision and Dahua Video Surveillance The ban on government uses, which takes effect ‘not later than one year after … enactment,’ applies not only to future uses of Dahua and Hikvision equipment but also to legacy installations. The bill calls for an assessment of the current presence of the banned technologies and development of a ‘phase-out plan’ to eliminate the equipment from government uses. 2. Motorola Makes A Splash With Avigilon Video Surveillance Acquisition Early clues point to Motorola positioning Avigilon as part of a broader solution, especially in the municipal/safe cities market. The company says the acquisition will enable more safe cities projects and more public-private partnerships between local communities and law enforcement. Motorola sees Avigilon as ‘a natural extension to global public safety and U.S. federal and military’ applications, according to the company. 3. Impact Of Data-Driven Smart Cities On Video Surveillance One of the major areas of technology that is going to shift how we interact with our cities is the Internet of Things (IoT). One benefit will be the ability to use video surveillance to analyze data on large crowds at sporting events The IoT already accounts for swaths of technology and devices operating in the background. However, we’re increasingly seeing these come to the forefront of everyday life, as data becomes increasingly critical. Bosch is highlighting its “Simply. Connected” portfolio of smart city technology to transform security as well as urban mobility, air quality and energy efficiency 4. CES 2018: Security Technologies Influencing The Consumer Electronics Market Familiar players at security shows also have a presence at the Consumer Electronics Show (CES). For example, Bosch is highlighting its “Simply. Connected” portfolio of smart city technology to transform security as well as urban mobility, air quality and energy efficiency. Many consumer technologies on display offer a glimpse of what’s ahead for security. Are Panasonic’s 4K OLEDs with HDR10+ format or Sony’s A8F OLED televisions a preview of the future of security control room monitors? 5. SIA Predicts Top Physical Security Trends For 2018 Traditional security providers will focus more on deepening the customer experience and enhancing convenience and service. The rise of IoT also places an emphasis on cybersecurity, and security dealers will react by seeking manufacturers and technology partners with cyber-hardened network-connected devices. 6. High-Speed Visitor Screening Systems Will Improve Soft Target Security The system is more expensive than a metal detector, but about a third the cost of familiar airport body scanners. Labor reduction (because of faster throughput) can help offset the system costs, but “it’s difficult to quantify the improvement in the visitor experience,” says Mike Ellenbogen, CEO of Evolv Technology. 7. How To Prevent ATM Jackpotting With Physical And Cyber Security A new crime wave is hitting automated teller machines (ATMs); the common banking appliances are being rigged to spit out their entire cash supplies into a criminal’s waiting hands. The crime is called “ATM jackpotting” and has targeted banking machines located in grocery shops, pharmacies and other locations in Taiwan, Europe, Latin America and, in the last several months, the United States. Rough estimates place the total amount of global losses at up to $60 million. The safety and security world bring a complex problem to solve how to pick out a face in a moving and changing environment and compare it to several faces of interest 8. Why We Need To Look Beyond Technology For Smart City Security Solutions Although technology is necessary for an urban area to transition in to a safe and smart city, technology alone isn’t sufficient. Truly smart cities are savvy cities and that includes how they employ software, sensing, communications and other technologies to meet their needs. 9. How New Video Surveillance Technology Boosts Airport Security and Operations Employing airport security solutions is a complex situation with myriad government, state and local rules and regulations that need to be addressed while ensuring the comfort needs of passengers. Airport security is further challenged with improving and increasing operational efficiencies, as budgets are always an issue. As an example, security and operational data must be easily shared with other airport departments and local agencies such as police, customs, emergency response and airport operations to drive a more proactive approach across the organization. 10. The Evolution Of Facial Recognition From Body-Cams To Video Surveillance The safety and security world bring a 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.