37 Facts About Face recognition

Facial recognition system is a technology capable of matching a human face from a digital image or a video frame against a database of faces, typically employed to authenticate users through ID verification services, works by pinpointing and measuring facial features from a given image.

Since their inception, facial Face recognition systems have seen wider uses in recent times on smartphones and in other forms of technology, such as robotics.

Facial Face recognition systems have been deployed in advanced human–computer interaction, video surveillance and automatic indexing of images.

Facial Face recognition systems are employed throughout the world today by governments and private companies.

The use of facial Face recognition systems has raised controversy, with claims that the systems violate citizens' privacy, commonly make incorrect identifications, encourage gender norms and racial profiling, and do not protect important biometric data.

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Until the 1990s, facial recognition systems were developed primarily by using photographic portraits of human faces.

In 1997, the PCA Eigenface method of face recognition was improved upon using linear discriminant analysis to produce Fisherfaces.

Purely feature based approaches to facial recognition were overtaken in the late 1990s by the Bochum system, which used Gabor filter to record the face features and computed a grid of the face structure to link the features.

Some face recognition algorithms identify facial features by extracting landmarks, or features, from an image of the subject's face.

Three-dimensional face recognition technique uses 3D sensors to capture information about the shape of a face.

One advantage of 3D face recognition is that it is not affected by changes in lighting like other techniques.

Different form of taking input data for face recognition is by using thermal cameras, by this procedure the cameras will only detect the shape of the head and it will ignore the subject accessories such as glasses, hats, or makeup.

Current thermal face recognition systems are not able to reliably detect a face in a thermal image that has been taken of an outdoor environment.

Face recognition has been leveraged as a form of biometric authentication for various computing platforms and devices; Android 4.

In May 2017, a man was arrested using an automatic facial Face recognition system mounted on a van operated by the South Wales Police.

Live facial Face recognition has been trialled since 2016 in the streets of London and will be used on a regular basis from Metropolitan Police from beginning of 2020.

In recent years Maryland has used face recognition by comparing people's faces to their driver's license photos.

In 2006, the Skynet Project was initiated by the Chinese Government to implement CCTV surveillance nationwide and as of 2018, there has been 20 million cameras, many of which capable of real-time facial Face recognition, deployed across the country for this project Some official claim that the current Skynet system can scan the entire Chinese population in one second and the world population in two seconds.

In 2018, Chinese police in Zhengzhou and Beijing were using smart glasses to take photos which are compared against a government database using facial Face recognition to identify suspects, retrieve an address, and track people moving beyond their home areas.

Many public places in China are implemented with facial Face recognition equipment, including railway stations, airports, tourist attractions, expos, and office buildings.

In 2019, Protestors in Hong Kong destroyed smart lampposts amid concerns they could contain cameras and facial Face recognition system used for surveillance by Chinese authorities.

The face recognition system is deployed to identify individuals among the travelers that are sought by the Panamanian National Police or Interpol.

Face recognition systems "made in China" were deployed at the 2016 Summer Olympics in Rio de Janeiro.

In 2019, facial Face recognition to prevent theft was in use at Sydney's Star Casino and was deployed at gaming venues in New Zealand.

In June 2022, consumer group CHOICE reported facial Face recognition was in use in Australia at Kmart, Bunnings, and The Good Guys.

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Face recognition systems have been used by photo management software to identify the subjects of photographs, enabling features such as searching images by person, as well as suggesting photos to be shared with a specific contact if their presence were detected in a photo.

In 2019, casinos in Australia and New Zealand rolled out facial Face recognition to prevent theft, and a representative of Sydney's Star Casino said they would provide 'customer service' like welcoming a patron back to a bar.

Facial Face recognition systems have been criticized for upholding and judging based on a binary gender assumption.

Face recognition can be used not just to identify an individual, but to unearth other personal data associated with an individual – such as other photos featuring the individual, blog posts, social media profiles, Internet behavior, and travel patterns.

In 2019, the Financial Times first reported that facial Face recognition software was in use in the King's Cross area of London.

However, another study showed that several commercial facial Face recognition software sold to law enforcement offices around the country had a lower false non-match rate for black people than for white people.

In March 2020 California residents filed a class action against Clearview AI, alleging that the company had illegally collected biometric data online and with the help of face recognition technology built up a database of biometric data which was sold to companies and police forces.

The coalition calls for a ban on facial Face recognition and launched a European Citizens' Initiative in February 2021.

The research on automated emotion Face recognition has since the 1970s focused on facial expressions and speech, which are regarded as the two most important ways in which humans communicate emotions to other humans.

Research into automatic emotion specific expression recognition has in the past decades focused on frontal view images of human faces.

In 2016, facial feature emotion recognition algorithms were among the new technologies, alongside high-definition CCTV, high resolution 3D face recognition and iris recognition, that found their way out of university research labs.

Development of anti-facial Face recognition technology is effectively an arms race between privacy researchers and big data companies.