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Facial Recognition: Why Is It So Controversial?

Author: huifan   Time: 2021-01-15

Face recognition. Facial recognition is a convenient way to unlock mobile phones or computers, but people are becoming more and more controversial about facial recognition. The city of San Francisco has effectively banned the use of facial recognition by police and other agencies. Microsoft deleted a complete face database, which contained more than 10 million images. ACLU has been calling for more supervision and protection in terms of facial recognition technology.

How does this facial recognition technology even work, and why is it controversial?

If you are a student studying IT, then you may dabble in facial technology in your future career. Therefore, it is important to understand this technology and what may happen in the future.

How does facial recognition work?

Facial recognition technology can identify people from photos or videos. It compares selected facial features with faces in the database, and can analyze facial texture and shape to verify the person.



Facial recognition is performed in two steps. 

Step 1 is to extract and select features from the image. 
Step 2 is the classification of objects or features.
There are many ways that facial technology works in different products and applications, including:
  • Traditional.
Many traditional facial recognition algorithms recognize facial features, such as the position or size of eyes, nose, cheek bones, and chin. These functions are used to connect with other matching functions. Some algorithms only save facial data that is important for facial recognition, rather than the entire image of the face. Traditional algorithms have two main methods, geometric method or photometric method. Geometric algorithms focus on distinguishing features. Photometry is a statistical method that puts an image into values, and then compares these values   with a template during the elimination process. Either way, these algorithms use facial images for comparison and contrast, matching the correct image for facial recognition.
  • 3D recognition. 
Three-dimensional face recognition uses a 3D sensor to capture information about the shape of the face. From there, the software recognizes unique features such as eyeballs, nose and chin. Light or other changes in the surrounding environment will not affect 3D facial recognition, but facial expressions may cause some sensitivity. Therefore, cameras that use this technology to recognize different angles of faces in real time are becoming more and more popular.
  • Skin texture analysis. This is an emerging trend in facial recognition. This process turns the unique lines and patterns on a person's skin into a mathematical space. A photo of a piece of skin was taken, and the skin piece was divided into smaller pieces. The algorithm converts the patch into a mathematical space, and then compares the skin patch with the database.
  • Thermal imager. The thermal imager only detects the shape of the head and ignores accessories such as glasses or hats. The thermal imager can take images even in low light without using a flash. But the database of hot face recognition is limited, so it is difficult to use. If hot facial recognition technology becomes more and more popular and the database can be expanded, then it may be an excellent choice.
Both methods have their pros and cons, and many companies are trying to combine different methods to increase success rates. Combining these methods means that facial expressions, blinking, frowning or smiling, race, gender, and even facial hair or glasses can be considered.
Huifan facial recognition device

The history of facial recognition.

Facial recognition was founded by Woody Bledsoe, Helen Chan Wolf and Charles Bisson as early as the 1960s. These early pioneers worked to create computers that could recognize human faces. Their initial facial recognition method involves manually marking landmarks on the face, such as eyes and mouth, and then mathematically rotating them through a computer to compensate for different postures. The distance between landmarks is automatically taken into account and comparisons are made between images. Over time, this technology began to arouse the interest of others.
In 1991, Turk and Pentland proposed an eigenface method for facial recognition. The method involves using principal component analysis to take basic images and linearly combine them to reconstruct them. Eigenface methods use computer skills, matrices and high-dimensional spaces to create face recognition opportunities.
Other technical experts accepted this idea and developed software to promote the development of facial recognition. University students and laboratory professionals are committed to developing new facial recognition technology.
By 2001, face recognition had become mainstream. In the Super Bowl game that year, Florida police used facial recognition software to search for potential criminals and terrorists. 19 people were found to have minor criminal records.

Who is using facial recognition technology?

Facial recognition technology has been used by many organizations
  • Social media. For entertainment and entertainment, social media platforms use facial recognition technology to allow users to apply filters that can change their appearance.
  • Law enforcement. There are more than 117 million photos in the US government’s driver license photo database. With the help of facial recognition technology, criminals can be identified, security can be enhanced, and even more.
  • Mobile phone company. Mobile phones use facial recognition as another element of device security. Just like a fingerprint, your face can also be used as a unique identifier to unlock or lock the device.
  • Airport. The airport uses facial recognition technology to monitor criminals or criminals on the "no-fly" list. They can also use it to match tickets, passports and individuals, and find out the cause of the problem.
  • Business. Security is usually the main function of companies that use facial recognition technology. They are committed to ensuring the safety of the store and being able to identify anyone who causes simple surveillance issues.
  • Marketing personnel. Marketers help their customers promote facial recognition technology on social media, which can make their customers recognized by the public


HFSecurity face recognition device

Why does facial recognition technology have so many objections?

So, what factors make facial recognition technology controversial?It seems to help consumers bring convenience and provide assistance in safety measures. However, every professional that comes with facial recognition software has a drawback.
When it comes to facial recognition, privacy is a major concern for many people. Naively use Facebook's photo tools to tag your friends, allowing you to use facial recognition technology, which may be used without your knowledge. Experts say that people will be shocked by how to use facial recognition technology. And there are few regulations on facial recognition, which means that companies should not follow the rules for maintaining personal privacy. For many advocates, privacy violations are the primary consideration for this technology.
Similarly, the facial recognition database is not immune to hacking. This means that the information may fall into the wrong hands and then be used maliciously. Other governments and hackers can also access your picture and all the information stored with it, including your driver's license number, license plate, etc. If used improperly, such information can be dangerous. Cyber   security measures will have to continue to become stronger to protect all this facial data and deter hackers.
In the end, the software is not perfect and can go wrong. This can lead to people being wrongly accused or accused of crime, which is a huge problem. Facial recognition software may have two kinds of errors, false positives or false positives. A false negative means that the software cannot match someone's face in their database. False positives are when the system recognizes a face but the match is actually incorrect. Both of these errors can cause huge problems for organizations that use software and the general public.

The future of face recognition.

So in the face of the controversy surrounding facial recognition, what will be the future? Many types of organizations from shopping, banking and travel said they will continue to use facial recognition software. The key will be the entry of well-trained IT professionals into the workplace, who can help formulate regulations, improve security and privacy, and adopt new versions of more accurate facial recognition.
If you are interested in participating in technological innovation and participating in upcoming new technologies, having an IT degree can help you. The right degree can help you train yourself and provide marketable knowledge for your dream career, which is essential to help you stand out from the competition.
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