With the proliferation of embedded and physical cameras and a continuing exponential increase in computing power, facial recognition (FR) is becoming an important tool for many applications involving people and cameras.
There have been significant advances in leveraging some of the latest in Artificial Intelligence technology for facial recognition, which has also been enabled by advances in technology. This has come about as facial recognition systems have nearly absolute precision in ideal conditions, reaching a 99.97 per cent recognition accuracy level, according to research published by the Centre for Strategic and International Studies (CSIS).
However, it has to be noted that in most real-life scenarios, the conditions are far from ideal. Accuracy can commonly be lower even with more advanced algorithmic techniques – especially with regard to CCTV in public places.
Facial recognition capability can be divided into two types: FR-1 and FR-N. FR-1 identifies in a binary way if a person is the hypothesised one (mainly for authentication) and FR-N is to detect if the person is from a database of a certain number of faces. With FR-N, the size of the database can typically range from a dozen, as with a small enterprise, to millions of people in a large city.
Given the current pandemic, the inherent contactless nature of FR makes it a highly desirable alternative to fingerprint scanners and even RFID cards for office access and/or attendance monitoring. Many buildings, construction sites and enterprises within Singapore, in particular, but also within Southeast Asia (SEA) are now beginning to use FR-N for Access Control and when applicable, for their attendance management by leveraging CCTV installed at entrances.
They can also have a full-featured AI-powered solution on these same CCTVs, which may include from mask compliance and social distancing to attendance management and various other video analytics to improve security, safety and streamline office operations. There are a number of malls within SEA which is now closely looking into leveraging this technology.
Schools and higher institutions of learning, including universities have shown strong interest to leverage similar solutions for attendance management, apart from bringing in various other video analytics to improve security and safety in the campuses and hostels.
One of the top universities in Singapore is currently trialing the use of different attributes within facial recognition such as gender and age group, to obtain intrusion alerts within sensitive zones of the university.
Within the transportation segment, Singapore’s Changi Airport already leverages FR-1 at the immigration checkpoints, and also at automated immigration clearance gates which are expected to be fully unmanned. Increasingly, we are seeing more airports within SEA beginning to trial AI-powered video technology to identify consumer sentiments and experiences within the airports.
The ports within SEA, such as the Philippines and Malaysia, will also be deploying FR-N as part of their staff and visitor management.
The ride-sharing industry has also adopted facial recognition to bring an added layer of verification and security to rides. Grab, a ride-hailing company based in the region, has also incorporated facial recognition technologies to accurately identify the right drivers and passengers for each ride.
FR-1 is now increasingly being leveraged within the banking industry. OCBC now allows users to access their bank balances at ATMs simply by typing in their NRIC and facing the camera at the ATM. We predict public announcements from some of the other banks within this year.
Indonesia and Singapore are actively piloting FR-N for various large events slated this year. Participants simply upload their picture onto a portal and the FR-N at the registration kiosk will be able to identify the person, The FR-N system thus registers attendees without requiring face-to-face interactions.
This helps reduce the amount of physical contact between event staff and attendees and minimise touchpoints at registration kiosks. Further using the CCTV’s within the event site, if there are breaches in safe-distancing rules or mask compliance, the reminders or alerts will be sent.
The key use of facial recognition is on intrusion systems that detect if someone enters a home or workplace when an intrusion alarm is left armed. When installed in personal properties like housing estates, it also comes with the feature of enabling individual blacklists and whitelists for different locations and entry points, thus preventing any unidentified individual from entering the premises and eliminating trespassing or intrusion.
This can easily be expanded to prevent people who are not compliant with mask usage from entering the complex. There are different trials ongoing within SE Asia.
Although at an early stage, some retailers and fast-food chains in Thailand are beginning to leverage FR technology. Facial Recognition allows retailers to capture what shoppers are looking at in physical shops, obtain their sentiments allowing actionable reports to on-ground retail operators. Similarly, various customer experience metrics from entry to pick-up and exit can be obtained leveraging FR for fast food restaurants.
If there are concerns amongst citizens, it relates to the unanticipated use of FR with the different CCTV’s and monitoring their private pursuits. It is to be noted that even with CCTV’s with an FR system, this will be as safe and regulated as having security guards watching the people coming in within the site.
Responsibly used, FR Technology can protect people, enterprises, and society in Singapore and Southeast Asia. Facial analytics will continue to build in importance with the continued ubiquity of cameras and other video sensors, even as the associated technical challenges and required capabilities grow.
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