12 Things You Need To Know About Facial Recognition Technology

 

Facial recognition technology, or FRT,is a technology that is rapidly used in different fields, like defense, social media, fintech, and more. Statistically, the FRT Industry acquired around USD 3.8 billion of global revenue in 2020, and the count is growing further each year. In fact, 80% of governments globally utilize FRT technology in some capacity besides other commercial uses.

The technology involves use of Machine Learning that analyses human faces to find matches with recorded images in databases.

The reach and uses of facial recognition apps are more extensive than that globally. Wondering about the full expanse of this identity verification system and why it is vital? Read ahead to know all details. 

What is Facial Recognition Technology?

Facial recognition is a type of biometrics technology-centric solution for detecting the identity of people by their faces. Organizations use this technology as a modern security solution to avoid fraudulent activities. 

(Source)

While facial recognition was in practice in some capacity for a long time, it recently noticed a contemporary modification with artificial intelligence and IoT solutions. Deep learning, face analysis, pattern recognition, and machine learning contributed highly to its advancement. 

Things to Know about Facial Recognition Technology

There are multiple points about FRT that you should know to grasp what it stands for fully. All are detailed here. 

1. The working mechanism of FRT 

The FRT system utilizes a biometrics-enabled AI algorithm to create templates for the person’s face. Then, it compares the facial traits from videos or photographs. Typically, it takes pictures in the database for cross-examination and verifies people's identities.

2. The procedure of FRT systems 

• Detecting the face- The system detects the person's face.

• Face analysis- Next, the software scans the facial geometry and notes points like the distance of the chin to the forehead, space between eyes, etc. 

• Converts image to coded data- It finds the main facial landmarks to prepare a facial signature by turning the analyzed points into a mathematical formula. The facial signature is comprised mainly of codes and is known as the unique faceprint.

• Match verification- The FRT system looks through the existing database of known facial images to find the one that aligns most with landmarks to bring an appropriate match. 

(Source)

3. Main elements of reliable matching  

For full facial verification matching, the biometrics in the FRT systems include various features in a combined form. These elements include:

• Eye-zone recognition 

• High recognition and short processing time

• Neural network equipment-based recognition

• Vantage point 

• GLVQ-centric multi-face detection and matching 

• Recognition of faces regardless of different expressions, beards, glasses, etc. 

4. Useful for age verification and protection of minors 

In many sites and apps, the age verification prompt is given aside from other identity-checking solutions. However, some minors do manage to sidestep these protection steps by providing the ID documents of elders. This way, they can access places they are prohibited from since those are adult-oriented establishments.  

With facial recognition, this is harder to do since the technology detects the face of people to verify their identity. 

5. Different use cases of FRT 

Facial recognition technology is used in different types of places and programs. The entrances of businesses can have this technology for additional security, and so do the departure gates at airports.

Plus, digitally, social media apps also use FRT algorithms for ID verification. Stores, colleges, and app development companies also utilize this solution. 

(Source)

6. Accuracy is above 90%

With FRT, identity verification has around 0.1% or a lower error rate. However, in real-world scenarios, multiple external factors can drop the accuracy rate of the FRT solutions. Typically, the error rate in such situations stays at around 10%. 

The cases that cause this include factors like lighting changes, makeup, and aging, which work against the software. Plus, if the person's eyes are closed and looking sideways, the camera cannot pick up the full image. That can also reduce the accuracy rate. 

7. FRT systems do have biases. 

The AI-based technology of the FRT systems utilizes deep learning and machine learning capabilities. So, the data it is trained with is what the software relies on primarily. Therefore, certain biases do form in the software function.

With the help of the right developers, you can expect a better bias detection process for fair usage. 

8. The tools can detect objects 

While the FRT apps and tools are useful for human face recognition, the technology can be expanded to detect other items as well. Some users try out devices with this technology for recognizing objects with specialized training and categorization support. For example, the software detects and analyses objects based on recorded item categories in the database, like cars, ammunition, etc. 

9. Privacy is a concern 

While FRT has many uses, it does have limitations related to privacy protection. With this technology, strangers can find a person's name, occupation, and other details. Plus, governments have more control over these solutions and can use them to find individuals easily, even regular citizens. This is a problem for many people as it essentially harms their privacy limits. 

(Source)

10. Better customer experience 

Face recognition technology can improve customers' security and usage experience. However, there are regulations regarding how much the brands can utilize it. It is important to research the available laws related to it first. 

Conclusion 

Facial recognition is useful for quick ID verification and security. Many organizations use it for operational and safety benefits, but privacy concerns remain. Research the laws more and take the help of reliable developers for app development with this feature.