It is not a hidden fact that some biometric technologies are sparking the imagination just like face recognition. Due to artificial intelligence (AI) and Blockchain, face recognition is going to represents a significant digital challenge for all companies, organizations, and especially governments. Keeping all this in view, we are going to discover the seven face recognition facts and trends that are going to shape the landscape in 2019-2020.

Facial Recognition

Face Recognition- How It Works?

Wondering, how facial recognition works? Facial recognition is a process of identifying or verifying the identity of a person with their face. This is going to capture, analyze, and compare patterns based on the person’s facial details. This process helps us detect and locates human faces in images and videos. The face capture process will be transforming analog information that is face into a set of digital information depending on the person’s facial features.

In the case of facial biometrics, a 2D or 3D sensor will be capturing a face. It is then going to transform it into digital data with the help of an algorithm and before it compares to the image captured present in the database. Note that these automated systems will be used to identify or check the identity of individuals in a few seconds according to their facial features.

Source: How Does Facial Recognition Work?

For your information, owners of the iPhone X have been introduced to the facial recognition technology. The Face ID biometric solution developed by Apple was criticized in China in late 2017 because it was not able to differentiate between certain Chinese faces. Additionally, there are still more signatures via the human body that exists that include fingerprints, iris scans, voice recognition, digitization of veins in the palm and behavioral measurements.

Wondering, what is facial recognition used for? Now, we will be looking at the trends that you should know:

1- Best Facial Recognition Technologies

In the race for biometric innovation, there are several projects competing for the top spot. Facebook, Google, Apple, Amazon, and Microsoft (GAFAM) are very much in the race. It is interesting to note that all the software web giants regularly publish their theoretical discoveries in the fields of image recognition, artificial intelligence, and face analysis in an attempt to possibly understand it. Let’s have a deeper look:

Academia: The GaussianFace algorithm was developed in 2014 by researchers at The Chinese University of Hong Kong. They achieved facial identification scores of 98.52% in comparison to the score of 97.53% achieved by humans. It was an excellent score, despite the weaknesses regarding memory capacity required and calculation times.

Facebook and Google: Facebook, Google, Amazon, IBM, and more are the companies using facial recognition. In 2014, Facebook launches DeepFace program that determines whether two photographed faces belong to the same person or not with an accuracy rate of 97.25%. When humans took that test, the percentage of the correct answers was 97.53% of cases that was just 0.28% better as compared to the Facebook program.

Microsoft, IBM, and Megvii: A study conducted by the MIT researchers in February 2018 found out that Microsoft, IBM, and China-based Megvii  (FACE++) tools are having high error rates when identifying darker-skin women as compared to lighter-skin men. At the end of June 2018, Microsoft announced in a blog post that they have made solid improvements in their biased facial recognition technology.

Amazon: In May 2018, Ars Technica reported that Amazon is actively promoting its cloud-based face recognition service named Rekognition to law enforcement agencies. This system will enable you to could recognize 100 people in a single image and will perform face match against databases having tens of millions of faces.

2- Learning to Learn Via Deep Learning

The feature common that’s common to all the disruptive technologies is called Artificial Intelligence (AI) and more precisely deep learning where a system is able to learn from data.

Learning to Learn Via Deep Learning

According to the NIST report, massive gains inaccuracy was made in the last 5 years (2013- 2018) and exceed improvements were achieved in the 2010-2013 period. The majority of the face recognition algorithms in 2018 outperform the most accurate algorithm from 2013.​

3- Facial Recognition Markets

According to a study published in June 2019, it is stated that the global facial recognition market will be generating $7 billion of revenue that will be supported by a compound annual growth rate (CAGR) of 16% over the period of 2019-2024. For the period of 2019, the market is estimated at $3.2 billion. Note that the two biggest drivers of this growth are surveillance in the public sector and various benefits of facial recognition in diverse market segments.

Facial Recognition Markets

Top 3 Application Categories

Security/Law Enforcement: This market is led by the increased activity control the crime and terrorism. The benefits of facial recognition systems for policing are very clear as it helps in the detection and prevention of crime. Facial recognition will be used when issuing identity documents and mostly combined with other biometric technologies such as fingerprints.

Note that the face match is used at border checks for comparing the portrait on a digitized biometric passport with the holder’s face. The addition of face biometrics at the police checks but it’s used is rigorously controlled in Europe. In 2016, the “man in the hat” who was responsible for the Brussels terror attacks was identified due to the FBI facial recognition software. Furthermore, the South Wales Police implemented it at the UEFA Champions League Final in 2017.

Health: Significant advances have been made in this area. All thanks to deep learning and face analysis, it will help in tracking a patient’s use of medication more accurately and detection of genetic diseases like DiGeorge syndrome with a success rate of 96.6%. Furthermore, it will also support pain management procedures.

Marketing and Retail: In this area, the use of facial recognition was least expected. But possibly promises the most. Know Your Customer (KYC) is will be a hot topic in 2019. This trend is being combined with the latest marketing advances in customer experience. By placing facial recognition cameras in retail outlets, it is possible to analyze the behavior of shoppers and improving the customer purchase process.

Similar to the system recently designed by Facebook. In those systems, sales staff are provided with customer information picked from their social media profiles for producing the expertly customized responses.

4- Mapping of New Users

Without any doubt, the United States is offering the largest market for face recognition opportunities and the Asia-Pacific region is having the fastest growth in the sector. In this, China and India are leading in the field.

Face Recognition in China: Face recognition technology is definitely a new hot topic in China starting from banks to airports to police. Now authorities are planning to expand the facial recognition sunglasses program as police and they are beginning to use them in the outskirts of Beijing.

Furthermore, China is also setting up and perfecting a video surveillance network all over the country. Over 200 million surveillance cameras are in use at the end of 2018 and 626 million will be active by 2020. You can clearly see that China’s ambitions in AI (and facial recognition technology) is high. The country is working with an aim to become a world leader in AI by 2030.

5- Face Recognition Strengthening the Legal System

The ethical and societal challenges posed by data protection is radically affected by the use of facial recognition technologies.

EU and UK Biometric Data Protection: In Europe and the UK, the General Data Protection Regulation (GDPR) has provided a rigorous framework for these practices. Any investigations into a citizen’s private life or business travel habits are out of the question and any such invasions of privacy are carrying severe penalties.

Applicable from May last year, the GDPR is supporting the principle of a harmonized European framework, in particular protecting the right to be forgotten and the giving of consent through clear affirmative action. This directive is bound to get international repercussions.

6- Rebels – Facial Recognition Hackers

Despite this technical and legal arsenal is designed to protect data, citizens, and their anonymity. But still, some critical voices are raising. Some parties are having concerns regarding these developments. The important question here is can be facial recognition be fooled? Grigory Bakunov in Russia has created a solution to escape the eyes permanently watching our movements and confuse face detection devices. He has also developed an algorithm that will create special makeup to fool the software. However, he has decided not to bring his product to market after realizing how easily it could be used by criminals.

Rebels – Facial Recognition Hackers

In addition to this, Germany and Berlin artist Adam Harvey has come up with a similar device known as CV Dazzle. He is working on clothing featuring patterns for preventing detection. The hyperface camouflage will be having patterns in fabric like eyes and mouths to fool the face recognition system.

7- Further Together –Moving to Hybridized Solutions

The identification and authentication solutions of the future will borrow from all aspects of biometrics. This will lead to “biometrix” or a biometric mix that is capable of guaranteeing total security and privacy for all the stakeholders in the ecosystem.

This was a brief about the latest trends related to facial recognition. In the end, it’s on us how we are going to use it. It can be for the betterment or it can be misused. As a human, we are responsible for the advancement and problems related to it.