Facing the Future: Growth & Trends in Facial Recognition Technology 2020

The facial recognition market is estimated to be ~USD 4.3 billion in 2018 and growing at a CAGR of ~13.5% during the forecast period of 2019–2025. The facial recognition market is expecting a sudden boom due to the increased proliferation of technology in businesses. The technology market is driven mostly by businesses and government organizations as everything is being digitized certain mundane everyday activities such as security in less time and human interference. Face verification technology is expected to double by 2025

According to reports, face verification technology is being deployed in almost every sector from installation in smartphones to unlock screen to business sectors for security purposes, facial verification technology is fostering every sector.

Face Verification Technology-How it Works:

Facial recognition is verified human faces through technology that uses biometrics to map facial features from a photograph or video. it checks the details and important information with a database of selected faces to find a perfect match. Here is how it works:

• Capture: A picture of the face is captured from a photo, video or a good camera.
• Extraction: Facial recognition software maps the geometry of your face. This mapping measures the distance between facial features. This identifies facial landmarks that differentiate the face and get a facial signature.
• Comparison: The data is then compared to a database of known faces.
• Matching: The final step is decision making. Faceprint is matched to an image in a facial verification system database.

Functions of Facial Recognition Technology:

Facial recognition can be broadly categorized into three types of functions:

• Basic FR systems simply recognize the presence of a face for purposes such as applying Instagram filters or tagging in Facebook images. A camera looks for the defining features of a face (a pair of eyes, a nose, and a mouth), and algorithms help determine the direction and movement of the face, for example, whether the mouth is open or closed.
• Face Identification. These applications work by first storing an image of a person’s face by measuring the unique features that will identify it. To access a device or facility, the person must present their face again, and a facial recognition system measures their features and confirms their identity against the stored face.
• Face Searches. Some systems are used to identify unknown faces for security, advertising, or law enforcement purposes. They operate similarly to a face identification function, but instead of matching one person to one stored reference face, algorithms search an extensive database of faces to find a match.

Trends of Facial Recognition Technology to watch in 2020:

Following are some trends of facial recognition technology that one should know about in the year 2020:

2D vs. 3D Facial Recognition Systems:

Most FR software in use today relies on two-dimensional (2D) technology, namely, photographs or video images. These images are easy to obtain, for example, by using footage from a security camera or a person’s Facebook profile picture.

However, using 2D images for FR also has some drawbacks. Because photographs are flat, algorithms can measure certain features — such as the distance between a person’s eyes — but cannot measure depth or dimensions such as the length of a nose or a prominent chin. Additionally, 2D recognition systems are dependent on the visible light spectrum to acquire an image. If ambient lighting conditions are dark or murky, it can impede recognition accuracy.

The more recent emergence of three-dimensional (3D) sensing systems based on invisible near-infrared (NIR) light offers increased detail and eliminates reliance on ambient light. NIR-based facial recognition systems work by casting a pattern of tiny dots (created by shining near-infrared laser light through a filter, called a diffractive optical element or DOE) onto a person’s face. A NIR camera captures the reflection of those dots, using alterations in the reflected pattern and/or time of return to creating a 3D “map” of the person’s face.

Intelligent Shopping:

Data analysts and marketers might want to hold on to their hats since facial recognition takes market data to a whole new level by providing intelligent shopping capabilities. When it’s combined with Artificial Intelligence (AI), other data systems, or Radio Frequency Identification(RFID) technology, retailers can use facial recognition to serve up highly customized in-store experiences. As brick-and-mortar stores work to transform into destinations that will still entice customers, facial recognition can do even more than create a better experience for shoppers. It can also provide a treasure trove of data for marketers, who can use that information to make continual improvements.

Convenience & Security of Smartphones:

In our world of smartphones and personal technology use, Snapchat selfie addicts and the like have long been comfortable with face-scanning technology. Although this isn’t the same as the type of facial recognition we’ve been talking about, that acceptance has made it easier to introduce new personal uses for this technology into our everyday lives. Facial recognition seems to have passed a personal litmus test in this regard. Apple was the first major carrier to implement the use of facial recognition as a way to unlock a smartphone screen and then later to activate Apple Pay. Less than a year out from widespread release, Apple Face ID (along with most other major smartphone models and operating systems) has gotten people quite comfortable with using their faces to unlock phone features with a simple glance.

Facial Verification At Airports- Replacing Tickets

China has an estimated 200 million surveillance cameras and was quick to embrace the power of facial recognition in public spaces. American Airlines is using face recognition technology to board international flights of Dallas/Fort Worth International Airport (DFW). Most recently, the U.S. Customs and Border Protection Biometric Exit Program is now used in 17 airports. It’s projected to soon partner with more airlines, to be able to scan 97 percent of departing commercial passengers by 2023.

Facial recognition in airports works to streamline the check-in experience. Some travelers appreciate the convenience of not having to scramble for tickets, passports or driver’s licenses when herding a family and luggage through airport security. Hotels are considering using facial recognition systems to identify and even interact with guests, with 72% of hotel operators in one survey expecting to deploy such technology in the next four years.1 When guest belongs to loyalty programs, facial recognition can enable new levels of concierge service and perks.

Emerging Facial Recognition Use in Healthcare:

When biometric data is optimized and combed with artificial intelligence or machine learning capabilities, the possible applications are vast. In healthcare, deep learning, and face analysis have already made it possible to:

• Track a patient’s use of medication more accurately
• Detect genetic diseases such as DiGeorge syndrome with a success rate of 96.6%
• Support pain management procedures.

For health care providers in assisted living or memory care facilities, facial recognition can offer an additional layer of patient protection, for example, if a patient wanders off the property.