In an era characterized by threatening crimes in real-time and the web, facial recognition is gaining more significance than ever, in tandem with the robust digital transformation globally. The use of surveillance techniques for ensuring public safety and maintaining law and order has majorly changed over the last few years, with increasingly terrifying incidents worldwide, the attack of 9/11 being a major instance. While security systems had been good enough until a point, the occurrence of devastating crimes has instigated key advancements in security and surveillance software. Facial recognition technology, to that end, has made significant strides in recent years and has emerged to be one of the most reliable contactless biometric systems ever.
In laymen's terminology, facial recognition works exactly the way humans recognize faces – the only difference is it is done in a technical algorithmic way, where the software views your face as a collection of data. Your faceprint here is the information for the facial recognition software.
This is the first step. The face is first detected from a sea of faces – it might have been captured in a video as well, alone or in a crowd. You may be looking straight into the camera or maybe on the side. The facial recognition software takes note of the facial features using machine learning algorithms and deep neural networks.
Usually, the detection starts with the eyes, then the eyebrows, nose, and other facial features. Once facial regions and their measurements are detected, the software detects facial positions.
As the software reads facial geometry, it calculates the distance between your eyes, eyebrows, from the forehead to the chin, and so on. Facial landmarks are distinguished, and a facial signature is created using computer vision algorithms. Every facial landmark acts as a separate nodal point for the software as they are the key to identifying your face – each face has close to 80 nodal points.
Once the facial signature is created, the face is adjusted in position and size to match with the user's face. The software can accurately identify even a slight movement in the position or an expression change.
After your facial signature is created, all the key elements are fed into the software, and your face is compared to a database of many faces. The software generates a unique feature vector for each face in the numeric format. These codes are called Faceprint, and they help to uniquely identify the person among all the others in the database of enrolled users.
As per a May 2018 report, the FBI has access to 412 million facial images for searches. Reports claim that at least 117 million Americans have their faces enrolled in one or more police databases.
This is the final step. Here's where your face may match that of an image in the database, and your identity is determined. Since the database has all registered users, the software matches the unique vector code to the dataset, trying to match the exact features. If the compared featured vector value falls below a limit, the software returns the ID of the match found in the database.
Several businesses use facial recognition technology. Faces are often scanned at airports, for example, for identity verification. Automakers use facial recognition technology to prevent car thefts. The BFSI sector is a major example of how effectively facial recognition software encourages online banking and purchases.
Banks are lately turning onto facial recognition software, specifically for identity verification. With digitalization transforming the BFSI sector, online banking and virtual transactions are becoming more popular and essential than ever before. Many banks use facial recognition as secure login tools as it reportedly offers 'less than a one-in-a-million chance of mistaken identity', claim experts. Besides online banking, many banks offer facial recognition as a means to operate accounts through ATMs. This effectively eliminates the need for a card swipe as face scanning helps prevent frauds online.
Using facial recognition software gained even more prominence during the pandemic. As per estimates by research firm Aite-Novarica, out of 11,000 financial institutions in the United States, around 15% to 20% use selfie photo imaging alongside document verification for user authentication. In 2020, the firm claims that close to 600-700 more financial establishments adopted facial recognition technology.
2) Marketing & Advertising
In the marketing domain, face recognition can be deployed to collect demographic information about target audiences – especially people who stop and look at ads/hoardings. Face scanning advertising is all set to be the future, as ad targeting gets more precise. Using this technology will provide real-time analytics to advertisers, informing them about which products customers chose or even browsed. The software also helps retailers to know when certain items are low in stock.
As digitization becomes more and more pronounced, facial recognition can be built into phones and tablets to analyze facial expressions and serve various ads depending on the user's mood.
Recently, Walgreens announced that it is bringing new technology to the market that will embed sensors, cameras, and digital screens to its cooler doors, generating smart displays to target ads to individual customers. These sensors and cameras will be connected to suitable face-scanning technology that can collect user details such as age and gender.
For the same reason it is used in advertising, facial recognition is also expected to gain momentum in the retail spectrum. Retailers have unearthed a huge opportunity as they realized how beneficial linking facial recognition to user personalization could be. In a sense, face scanning will help capture shopper emotions, helping retailers understand what they are looking at, for how long, and with what expressions. Accordingly, they'll be able to generate suitable ads and promotions to shoppers through online mediums.
Using face scanning in retail outlets also helps encourage self-checkout systems, eliminating the need for extra staff. Additionally, this technology-enhanced consumer experience by providing a personalized ad customer-centric shopping offering. Facial recognition helps retailers understand consumer moods, especially when they view promotional offers or discounts, thereby helping them to offer tailored assistance to shoppers.
4) Law Enforcement
The field of law enforcement is one of the most well-known and predictable use-cases of facial scanning technology. In a nutshell, this software can help conduct faster investigations and prevent and resolve crimes. More often than not, law enforcement agencies use face scanning in routine policing, where the police collect mugshots from arrestees and then place them in federal face recognition databases. Once an arrestee's photo has been taken, the mugshot remains in one or more databases and will be scanned every time the police are involved in a criminal search.
When the law unearths people supposedly involved in illegal activity or suspicious events, it uses facial recognition software to identify them and to find if they are actually involved in any wrongdoings.
Helpful though it is, facial recognition technology is far from flawless. Amazon's software, for example, misidentified some Congressmen as criminals. However, there's scope for a lot of improvement. Amazon was granted a patent to explore additional layers of security, where the software asks users to perform certain actions that can later be combined with thermal imaging data or infrared image information for better user authentication.
Recently, face scanning is being used in educational institutions to make campuses safe from potential threats. Facial recognition cameras are used to better safety in schools and universities and streamline campus security. Many universities have been working on bringing about advanced face recognition techniques – for instance, Carnegie Mellon University has been working on technology to help better video surveillance.
Soon enough, facial recognition will be used in colleges to judge audience reactions and enable on-the-spot classroom analytics. Security will be tighter across schools and colleges by enabling face scanning. The software can analyze visitors' faces, and then, based on the results, they can be allowed or disallowed in the campus.
A useful and varied use-case of facial recognition in some educational institutions is that of ensuring attendance. In Australia, for instance, a company called LoopLearn has been helping certain schools to keep track of students and reduce the time spent on attendance reports.
Face scanning has had enormous scope in the automotive industry since its inception. Although the technology finds deployment mainly in self-driving cars, there is still a massive bandwidth for many other use-cases. For example, facial recognition technology can be used to monitor car temperature, change radio stations, start or stop the car, unlock the car when the owner approaches, and so on.
Facial recognition has proved to be extremely useful in the ride-hailing sector as it adds an extra layer of security. For instance, many Uber drivers use a face-scanning app to access their accounts and verify their identity in India. The information can then be passed to the rider so that they know they are driving with a verified individual.
Singapore-based ride-hailing firm Grab has recently partnered with Microsoft to incorporate facial recognition in its application to accurately identify drivers and passengers. Uber has also deployed Microsoft's technology to identify drivers and mitigate threatening incidents.
One of the best ways face recognition software can help the healthcare sector is to simplify the patient sign-in procedure. As opposed to standing in unnecessary queues or juggling forms, patients can be directly signed in with face-scanning software. There are more use cases in healthcare for this software, though. Researchers at Duke University have developed an Autism & Beyond app, which uses the iPhone's front camera as well as facial recognition algorithms to screen children for autism.
Apart from simplifying patient check-in and check-out procedures, face-scanning technology, from a futuristic viewpoint, can also be used to measure vital body signs. By simply looking at the camera, users will be able to monitor their blood pressure, measure their heart rate, stress level, etc. In the event that the pandemic or similar conditions resurface in the future, this technology could prove to be life-saving as it is contactless and non-invasive.
8) Air Travel
Air travel has massive scope for the implementation of facial recognition technology. One of the most predictable benefits of implementing this software is expediting TSA lines and a more tailored experience for all passengers. Using facial scanning is likely to prevent frauds using fake passports and possibly even avoid terrorists or illegal immigrants from boarding the aircraft. According to customs officials, facial scanning cameras have a 99% accuracy rate.
Many air travel companies have been testing the deployment of face-scanning software at airports for boarding. JetBlue has been implementing facial recognition technology instead of boarding passes and streamlining the overall process. Delta has also installed face-scanning kiosks to help passengers check their luggage.
1) DeepVision AI
This software collects footfall data across specific areas in cities by distinguishing among parameters such as gender, age, and ethnicity. It provides FRS solutions for planning and marketing as well as for businesses wanting to deploy facial recognition software for security. It also provides a real-time analytics dashboard, which can be personalized as needed.
The software boasts of an efficient Q&A service via email for web service integration queries. It also delivers 24X7 support and hands-on support from computer vision experts throughout the year.
Major brands mostly use DeepVision AI to target customers with personalized advertisements. It is also used by realtors, marketing agencies, and retail companies.
Betaface boasts of three major service offerings – customer software development services, facial recognition SDKs, and hosted web services. It mostly focuses on face and objection recognition and image and video analysis.
Betaface uses biometric measurements to track facial features on pictures and videos. It can also recognize emotion and ethnicity, in addition to being able to track facial features, skin, hair, and hairstyle shape. It also provides video surveillance and security software solutions.
Betaface is used by tech-savvy establishments and perhaps have their in-house development team that can integrate their application with an FRS if necessary. The software's consumer base includes entertainment agencies, web advertising companies, B2B software developers, and media content producers.
SenseTime provides stand-alone FRS services and face and body analyzing technology. It is particularly known for its high-accuracy solutions. Its service list includes the following:
· Liveness detection: It provides a user verification solution for preventing spoofing attacks.
· Facial feature point positioning: This service ensures that feature positioning is marked irrespective of movement, wide-angles, or changing expressions.
· Facial attributes: This service can conveniently recognize more than ten facial attributes.
· Body feature point: This service is used for body analysis; it uses 14 feature points to recognize various body parts, even during movement.
SenseTime is suited best for businesses that require extensive video-based facial recognition. Its customer base includes automobile and healthcare companies, advertising sector, and smart city planners.
4) Amazon Rekognition
Among most facial recognition software, Amazon Rekognition is one of the best ones there is. It deploys facial analysis and facial search for public safety and user verification. It is designed to identify objects and scenes by labelling them – it allows users to add personalized labels to objects and scenes as required, which ensures high success rates. What's more, it is extremely accurate, given that Amazon has a massive database at its disposal – in fact, it has a tested dataset to flag inappropriate content.
Amazon Rekognition also offers a special PPE detection feature used to help identify workers wearing PPEs for security. It provides face detection and analysis in live and stored videos as well.
Its customer base usually includes market research firms, media agencies, credit solutions, and e-commerce sites.
Face++ is one of most popular facial recognition software. Its service offering boasts of four types of technology solutions:
· Image beautify – to merge faces in multiple photographs
· Human body recognition – to detect skeletons, body outlines, and whole bodies
· Facial recognition – to detect, search, and compare faces
· Image detection – to tag faces on photographs
Face++ provides custom cloud services and APIs and SDKs to leverage these technologies. Among its API and SDK offerings are facial landmark information, face detection, 3D facial reconstruction, facial search and comparison, eye-gaze estimation, emotion recognition, and skin status analysis.
It is one of the best software for businesses where facial comparison using stored images is a priority. That's because it compares images with granular clarity, making it a natural choice for firms that are still attempting to integrate with FRS. Its consumers include the automotive sector, mobile phone companies, education sector, and online marketing agencies.
According to Juniper Research, demand for facial recognition hardware increases by 50% each year. By 2024, facial recognition solutions may be present in 1.3 billion devices or so. A score of companies worldwide is already using this extraordinary software, powered by technologies such as AI to authenticate payments and increase security. In the years to come, facial recognition technology will find deployment across a lot more verticals such as F&B, consumer electronics, event management, and the like, paving the path for commendable growth and success.