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A brief history of Facial Recognition

We’ve written widely about Facial Recognition in our Market Leadership section, but without ever looking back to the early beginnings of Facial Recognition or looking forward to what the future may bring.

Once considered a thing of science fiction, Facial Recognition is quickly becoming an integrated part of people’s everyday lives.

Several major industries have benefitted from the rapid advancements that have been made in Facial Recognition technology over the past 60 years and these include: law enforcement, border control, retail, mobile technology and banking and finance.

As we look forward to the future uses of Facial Recognition technology, it’s good to take a step back and see how far we have come since the early beginnings.

The dawn of Facial Recognition – 1960s

The earliest pioneers of facial recognition were Woody Bledsoe, Helen Chan Wolf and Charles Bisson. In 1964 and 1965, Bledsoe, along with Wolf and Bisson began work using computers to recognise the human face.

Due to the funding of the project originating from an unnamed intelligence agency, much of their work was never published. However it was later revealed that their initial work involved the manual marking of various “landmarks” on the face such as eye centres, mouth etc. These were then mathematically rotated by a computer to compensate for pose variation. The distances between landmarks were also automatically computed and compared between images to determine identity[1].

These earliest steps into Facial Recognition by Bledsoe, Wolf and Bisson were severely hampered by the technology of the era, but it remains an important first step in proving that Facial Recognition was a viable biometric.

Advancing the accuracy of Facial Recognition – 1970s

Carrying on from the initial work of Bledsoe, the baton was picked up in the 1970s by Goldstein, Harmon and Lesk who extended the work to include 21 specific subjective markers including hair colour and lip thickness in order to automate the recognition.

While the accuracy advanced, the measurements and locations still needed to be manually computed which proved to be extremely labour intensive yet still represents an advancement on Bledsoe’s RAND Tablet technology.

Using linear algebra for Facial Recognition – 1980s/90s

It wasn’t until the late 1980s that we saw further progress with the development of Facial Recognition as a viable biometric for businesses. In 1988, Sirovich and Kirby began applying linear algebra to the problem of facial recognition.

A system that came to be known as Eigenface showed that feature analysis on a collection of facial images could form a set of basic features. They were also able to show that less than one hundred values were required in order to accurately code a normalized facial image.

In 1991, Turk and Pentland carried on the work of Sirovich and Kirby by discovering how to detect faces within an image which led to the earliest instances of automatic facial recognition. This significant breakthrough was hindered by technological and environmental factors, however it paved the way for future developments in Facial Recognition technology.

FERET Programme – 1990s/2000s

The Defence Advanced Research Projects Agency (DARPA) and the National Institute of Standards and Technology (NIST) rolled out the Face Recognition Technology (FERET) programme in the early 1990s in order to encourage the commercial facial recognition market. The project involved creating a database of facial images. Included in the test set were 2,413 still facial images representing 856 people. The hope was that a large database of test images for facial recognition would inspire innovation and may result in more powerful facial recognition technology.

Face Recognition Vendor Tests – 2000s

The National Institute of Standards and Technology (NIST) began Face Recognition Vendor Tests (FRVT) in the early 2000s. Building on FERET, FRVTs were designed to provide independent government evaluations of facial recognition systems that were commercially available, as well as prototype technologies. These evaluations were designed to provide law enforcement agencies and the U.S. government with information necessary to determine the best ways to deploy facial recognition technology.

Face Recognition Grand Challenge – 2006

Launched in 2006, the primary goal of the Face Recognition Grand Challenge (FRGC) was to promote and advance face recognition technology designed to support existing face recognition efforts in the U.S. Government[2].

The FRGC evaluated the latest face recognition algorithms available. High-resolution face images, 3D face scans, and iris images were used in the tests. The results indicated that the new algorithms were 10 times more accurate than the face recognition algorithms of 2002 and 100 times more accurate than those of 1995, showing the advancements of facial recognition technology over the past decade.

Social Media – 2010-Current

Back in 2010, Facebook began implementing facial recognition functionality that helped identify people whose faces may feature in the photos that Facebook users update daily. The feature was instantly controversial with the news media, sparking a slew of privacy-related articles. However, Facebook users by and large did not seem to mind. Having no apparent negative impact on the website’s usage or popularity, more than 350 million photos are uploaded and tagged using face recognition each day.

iPhone X – 2017

Facial Recognition technology advanced rapidly from 2010 onwards and September 12, 2017 was another significant breakthrough for the integration of facial recognition into our day to day lives. This was the date that Apple launched the iPhone X – the first iPhone users could unlock with FaceID – Apple’s marketing term for facial recognition.

NEC and Facial Recognition

Border controls, airlines, airports, transport hubs, stadiums, mega events, concerts, conferences. Biometrics are playing a growing role not only in the real-time policing and securing of increasingly crowded and varied venues worldwide, but also in ensuring a smooth, enjoyable experience for the citizens who visit them.

As a long-time committed pioneer of biometric research and solutions, NEC has developed multi-modal technologies including face, iris and voice recognition, finger and palmprint identification, and ear acoustic authentication, and supplemented them with AI and data analytics to enhance situational awareness and facilitate effective real-time or post-event action in both law-enforcement and consumer-oriented spheres.

Face recognition can often prove one of the best biometrics because images can be taken without touching or interacting with the individual being identified, and those images recorded and instantly checked against existing databases.

NEC’s face recognition offers high-performance, scalable solutions for the most demanding real-time or post-event requirements. With face surveillance, search, identification and verification functions all on a single platform, it can be easily integrated into existing surveillance systems to extract faces in real time, match against an existing database or watchlist and produce real-time alerts to help reduce public safety risks.

With the ability to process and analyse multiple camera feeds and thousands of faces per minute, NEC’s powerful face recognition is able to address the largest and most difficult security challenges with unparalleled efficiency, sensitivity, and perception.

NEC Face Recognition in Action

In response to booming demand for varied biometrics, NEC has expanded its traditional range of face recognition applications from law-enforcement and security provision to new areas, and now boasts more than 1,000 active systems in over 70 countries and regions spanning police, immigration control agencies, national ID, banking, entertainment, stadium, conference venue systems, and many more.

Right now, many of our face recognition technology solutions are blazing a trail for first-time use in new areas and venues worldwide, such as end-to-end airport travel experiences in the U.S., mega event surveillance in Japan, and EU Summit security in Europe.

In 2019, NEC was named Frost & Sullivan Asia Pacific Biometrics Company of the Year in recognition of its leading position in the industry and foresight in innovating and developing future face recognition biometric solutions that maximize customer value and experience.

Balancing security and privacy

As the leading global pioneer of face recognition and other biometric technologies, and champion of our NEC Safer Cities Vision, NEC is fully vested in developing biometric recognition solutions and services that contribute to the creation of safe, secure, equal and efficient communities around the world.

Having positioned safety business as one of our key pillars of growth, we are keen to encourage businesses, consumers, and governments to work together to help balance the need for privacy with the benefits of protecting our society, securing our borders and providing consumer convenience without the fear of negative consequences.

At NEC, we strongly believe that face recognition can add significant value to our lives, and we seek to advance these technologies in ways that respect the worldwide principals of freedom, justice, rights to privacy, transparency and continuous improvement.

The future of Facial Recognition Technology

As we move into 2020, facial recognition technology continues to develop at pace and the uses of the technology are becoming more widespread. In a recent post, we looked at the eight trends to look out for with Facial Recognition in 2020. These included:

  1. Retail
  2. Hospitality and Resorts
  3. ATMs
  4. Digital Advertising
  5. Bus Safety
  6. Airlines
  7. Personalised Customer Experience
  8. Staffless Stores

Make sure you read our posts and find out how each of these sectors above are embracing facial recognition technology and putting it to great use.

Used in the right way, facial recognition technology can make a huge difference to all our lives and the way we experience so many things.


[1] de Leeuw, Karl; Bergstra, Jan (2007). The History of Information Security: A Comprehensive Handbook. Amsterdam: Elsevier. pp. 264–265

[2] https://www.nist.gov/programs-projects/face-recognition-grand-challenge-frgc

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