The global facial recognition market is expected to grow to USD 7 Billion by 2024 as per an industry report. Driven by its adoption in security and biometrics, facial recognition technology has now expanded its grip on several other use-cases such as marketing, healthcare and more. The human face is a sophisticated multidimensional structure that can convey a lot of information about individual expressions, facial features and feelings. Apart from recognizing a person, facial recognition technology is expanding its scope by estimating emotions and behavior. This article gives a short overview of key trends that are driving this change and then deep dives into how various industries are adopting facial recognition technology.
Key Trends Driving Increased Adoption of Facial Recognition & Facial Analytics Technology
There are top three factors that driving increased adoption of facial recognition technology across segments:
Advancements in technology
AI and more precisely deep learning have been driving the advancements in face recognition/analytics technology. While traditional facial recognition systems had their loopholes, advanced facial recognition systems today deliver far superior accuracy. For example, on a very well-known dataset in the industry (LFW), Facenet achieved an accuracy of ~99.63%. As the technology matures, it is seeing wider adoption across industries.
Availability of high performance, low cost embedded AI processors
While facial recognition technology has been around for a while now, it is only in recent years that we have seen true edge implementations of the same. Several high-performance embedded processors with the ability to run machine learning/deep learning algorithms have cropped up. They are driving down the overall cost of implementation of these systems without degrading the solution accuracy.
Expanding use-cases of technology (facial analysis)
While facial recognition technology has traditionally been used for biometrics purposes i.e. identifying and authenticating a person, recent years have seen an expansion in use-cases where this technology is significantly contributing. For example, marketers are using the facial analysis to understand user’s expressions and their eye gaze. Healthcare professionals are using the technology to estimate the amount of pain a patient is suffering from. The use-cases of facial analysis technology are endless and ever-expanding.
How Various Industries Are Adopting Facial Recognition & Facial Analytics Technology
Facial recognition is finding its widest adoption in access control, attendance tracking law enforcement and monitoring across industries. However, industries like retail are increasing adopting facial analysis to track user behavior. Let us do a deep dive into how various industries are adopting these technologies to drive results.
Figure 1: Industries adopting facial recognition and facial analytics
The retail industry is at the forefront of innovative uses of artificial intelligence (AI), augmented and virtual reality. Not only do AI and XR tools increase business efficiency, but they also provide an opportunity with customized interactions and convenience that their customers desire. Facial recognition and analytics is an ideal tool for retailers. The advancements in these algorithms have introduced new revolutions with numerous use cases that benefit retailers about check-out free stores, face detection, face recognition, person detection, tracking and more to help them optimize customer experiences and day-to-day retail operations.
- Checkout free stores
- Customer count
- Glance time
- Heat- mapping
- Tracking experiences
- Employee management
The car’s intelligent driver assistance system includes in-cabin and exterior monitoring. With a driver-facing camera, the AI-powered facial recognition system keeps an eye on whether the driver is paying attention and is alert by monitoring gestures, facial expressions, body language, etc. Facial recognition has countless possibilities and is finding its way into the new generations of cars in an attempt to increase safety and convenience.
- Driver face identification
- In-cabin experience
- Driver face tracking & face analysis
- Child protection
- Driver safety
Financial service providers are legally required to enforce KYC measures. They need to know how much of a risk those people are likely to pose and who they are doing business with. In this regard, facial recognition technology is making its way for primary security & ID recognition and liveness detection, which can allow the customer to access all their bank accounts, contributing to a safe banking system.
- KYC – Employee verification
- Fraud Prevention
- Face biometrics for remote banking
Fleet operators are installing driver-facing cameras and can monitor drivers remotely. These systems could help you confirm compliance with safety enhancement and provide first-hand evidence in case of an accident, increasing operational safety to secure their vehicles.
PS: If you are looking to develop a video telematics solution with camera and imaging services, we can help you upgrade your in-vehicle cameras/dash cams. Please write to us at firstname.lastname@example.org
Education is the crux and soul of any society. Carrying a photo ID on campus may soon become a thing of the past with the advancement in AI-based facial recognition technology implemented on campus. Facial recognition enables classroom analytics during a lecture and better security on campus. Apart from emotion/face recognition for evaluation, attendance, etc., this technology can make student data more personal & powerful.
- Face ID for authentication
- Campus security
- Automated registration
- Attendance tracking
- Student emotion detection
The expanding application of biometrics devices in the healthcare sector is driving awareness about the safety and security of patients’ details and personal data. Considering the rapid growth, a verification process helps access/link patient’s medical records by using a secured identification and authentication technology such as fingerprints, face recognition, etc. to control the cases of fraud/breaches. It enhances the patient experience, empowers caregivers at the point of need and improves safety & security for healthcare providers, patients and visitors.
- Patient’s monitoring
- Patient management
- Hospital crowd management
The transportation sector deals with large volumes of passengers and it is very important to automate the identification and boarding pass verification process at the checkpoint as they are not only means of transportation but also targets for attacks. Therefore, it is critically important for facial recognition technology to be implemented without compromising on safety as these systems can be used to automate certain verification/authorization processes along with improving the customer journey.
- Passenger identification
- Passenger traffic analysis
- Biometric monitoring for crime & suspect
SECURITY & SURVEILLANCE:
Enterprises can build advanced security and management systems using facial recognition and analytics to streamline their physical access systems. A broad range of embedded cameras in combination with the development of AI-powered systems allows for a full replacement of traditional security measures, serving many use cases:
- Threat and intrusion detection
- Perimeter and asset monitoring
- Known individual detection
- Online & mobile identity verification
- Compare photo ID to selfie
- Fraud detection/anti-spoofing with facial liveness features
- Frictionless authentication with face recognition AI
Law enforcement uses facial recognition technologies as one part of AI-driven surveillance systems. This is an effort in the direction of modernizing the police force, information gathering, criminal identification, verification and dissemination among various police organizations. By comparing selected facial features of the image from an already existing database, automated face recognition systems help in sourcing automatic verification and identification of persons from digital sketches, images & video frames.
Facial recognition and facial analytics technologies are increasingly being adopted across industries to drive benefits that were never seen before. From retail to healthcare and from transportation to surveillance, industries are using these technologies for identification, authentication, emotion estimation and user management. We expect this adoption to grow and deliver innovation in areas that were never seen before.
PathPartner offers facial recognition and facial analytics SDK to identify people and analyze behavior based on facial characteristics. The solution is based on machine learning and deep learning technologies and makes it easy to add facial analysis to your applications encompassing a wide variety of the above-mentioned use cases. If you want to achieve any of the above use-cases, write to us at email@example.com
Further reading :
- Camera Tuning : Understanding the Image Signal Processor and ISP Tuning
- Role of Machine Vision technology in Packaging Industry
- 10 Amazing AI-Based Video Analytics Use Cases in Retail
- How to Integrate Industrial Robots and Machine Vision in Manufacturing: Beyond Industry 4.0
- Case study - Development of a Wireless Smart Home Monitoring Camera
- Image quality tuning
- Connected cameras
- Imaging algorithms
- Plug and play camera modules