The ultimate guide to face recognition
Author: huifan Time: 2020-12-18
With the revolution of machine learning, a new trend has emerged, which is called face recognition. When Apple announced its FaceID feature, everyone started talking and considering implementing face recognition anywhere (business, mobile apps, medicine, retail, etc.).
But how can you be sure that this technology is what you need without a thorough understanding?
do not worry! Today we will tell you what facial recognition is, how it works, and what are the different use cases of the technology. Just to say that after reading this article, you will become a true Jedi knight of face recognition.
What is face recognition
Face (or facial) recognition is a biometric recognition system that is used to identify or verify a person by real-time comparison and analysis of patterns based on a person's facial contour storage record.
How facial recognition works
Facial recognition systems have an input in the form of an image or video stream and an output in the form of identifying or verifying objects appearing in the image or video. There are many design methods for face recognition software, most of which have the following three main stages:
1. Detect
2. alignment
3. recognition
Detect
It is a computer that determines the position and size of a human face in any (digital) image. It can detect the features of facial recognition information and ignore all other things, such as buildings behind you, trees in the forest, and body boards. Therefore, the first thing the computer needs to do is to recognize whether there is a face in front of it.
Face detection is something that researchers have studied for some time. It all started in 1973, when Kanade proposed the "first automated system" approach. Since its discovery, several face detection methods have been invented.
Author method
Kanade's first automation system in 1973
Principal component analysis of Sirovich and Kirby in 1987
Turk & Pentland Eigenface in 1991
Etemad and Challapa Fisherface in 1996
2001 Viola and Jones AdaBoost + Haar Cascade
2007 Naruniec and Skarbek Gabor Jets
2001 became a breakthrough year for face detection, because the Viola-Jones object detection framework was the first algorithm to detect faces in real time.
The algorithm receives a photo as a set of data for the color value of each pixel. In order to find the position of the face in an image or video, it looks for a contrast area between the light and dark parts of the image-just like the bridge of the nose is usually lighter than the surrounding areas on both sides, that is, the eye sockets are darker than the forehead. By repeatedly scanning the image data and Calculate the difference between the gray-scale pixel values below the white frame and the black frame, and the program can detect the face.
alignment
The initial facial recognition attempts attempted to imitate this human method. The computer divides the face into visible landmarks called nodes, which include the depth of the eye sockets, the distance between the eyes, and the width of the nose. The differences between these areas will then be used to create a unique code, a photo of a person's own face. But there is a problem: you can't really get the same view of the face in two photos. Our faces are constantly changing, they are not static, just like fingerprints.
The solution to this problem is to create a 3D model of the human face. Therefore, alignment can be achieved by 3D modeling the human face and using the 3D model to deform the human face into a standardized frontal representation.
Recognition
The actual recognition is to classify the detected, aligned and normalized faces as known identities. Basically, it answers the question "Who?" First of all, it is composed of different stages of a deep convolutional neural network, and this stage can have many different representations. It pushes through multiple classifiers, receives data according to the pushed data, and then judges, authenticates and compares to find out the identity of the person. The final decision can be made by performing a simple threshold operation on the difference metric.
Use of face recognition technology
Access personal device
Using fingerprints to unlock mobile phones is now a common trend. But after Apple Event 2017, the world is interested in the next big thing, which is unlocking your personal device with its face. The iPhone 8 and iPhone X sparked a hype about facial recognition for mobile apps and phones, and it seems that it will continue for some time.
Unlock your car
Gartner predicts that by 2020, the number of IoT connected devices will reach 20 billion. The first example that comes to mind is a car. Today, cars can recognize and respond to the surrounding environment, and we are even used to this idea. Thanks to machine learning, driverless cars are everywhere. However, if they truly recognize the owner, it will be amazing.
Targeted advertising
Of course, without the help of the marketing team, any technological breakthrough is complete. The Mondalies International Supermarket in the United States is already experimenting with smart shelves. The cameras in the aisle can recognize your age and gender and use them to provide you with what you might want. This is the next level of targeted advertising.
market feedback
What you might not think of is that facial recognition can be used to judge a person’s level of engagement, which helps to discover the best way to connect with potential and existing customers.
For example, Wal-Mart has also participated in the competition of facial recognition technology. It will develop its own FaceTech system to gain insight into customer satisfaction. It is possible that someday in the future, this method will become a standard and programmed operation for all major retailers.
Protect data
Facial recognition provides us with a new way to protect important data. We should have seen a lot of movies, love, anime, and spies. I think we will remember at least one spy movie. In movies, we can have one of the popular mysteries, which is that the really important information is stored and can be recognized by face In the room.. Now, these technologies not only appear in great movies, but also exist among us.
Mental health diagnosis
In medicine, it will also help. Face recognition has done a good job in detecting diseases. But what about health problems that are not easy to diagnose? Mental health issues are one of them. Thanks to facial recognition technology, it is now easier to track the patient's expression and determine the degree of distress, and diagnoses can be made more accurately.
Likewise, those who are struggling with facial blindness (prosopagnosia) will benefit greatly from facial recognition technology.
For those of us who have forgotten their names, there is also an application called "NameTag" that allows people to take pictures and find their online profile for you.
Security tracking
Face recognition can be used for good reasons such as security tracking. This year, the Download Festival became the first outdoor event in the UK, with the purpose of scanning the crowd to find well-known troublemakers. During the festival, cameras were strategically placed to monitor 90,000 people. Shopkeepers are using similar software to create their own database of known shoplifters and alert them when they enter the shop.
Daycare
As parents, we all want our children to be sound-free. As daycare owners, we want to gain a reputation as a place of high trust. Face recognition software can verify the personal identity of the child.
Social robot interaction
The future is here, social robot assistants not only need to perform the necessary tasks, but also need to know its owner and understand people's emotions to get a better user experience.
Benefits of face recognition
No more fraud
We are constantly looking for new ways to prevent fraud. PIN, password and captured information are not enough. With the development of artificial intelligence and machine learning, it has become easier to deceive security systems. MasterCard is actually looking at whether taking selfies can be a viable way to verify credit card purchases.
Spend less money
When discussing business, the first question you will ask about face recognition is "How much will I spend?"
Well, face recognition is one of the cheapest biometric technology on the market.
Facial biometrics
Easy to use
Face recognition is known for its convenience and social acceptance. It is the only biometric technology that can operate without user cooperation. It is real-time, so all you need to do is look at the camera and then know who you are in a few seconds.
Reduce product loss
Facial recognition software can reduce product losses in stores. It can spot notorious shoplifters and notify security personnel so they can escort them out of the shop. It can also solve the problem of employee theft. When employees know that there is software that can capture them and notify the store owner, they are less likely to steal.
Disadvantages of face recognition
Loss of privacy
There is an elephant in the room. Our consensus on the function of face recognition is great and perfect, but there is nothing in the world that is forever. Every perfect event or food requires some price.. The price we pay is our privacy. Of course, we hope that social activities will be safer and the shopping experience will be better. But we are ready to remain vigilant at all times.
This technology is a very powerful tool, and unless we want all new creepy stalking behaviors to happen, it will never fall into the wrong hands.
In fact, Japan's National Institute of Information Technology has developed private glasses with special lenses to absorb light in an attempt to conceal the various functions of facial recognition software. But this technique may already be redundant. FaceIt Argus can recognize the identity of your skin. This technology is called "Surface Texture Analysis", and it works like facial recognition, but it actually creates "skin patterns", which is really difficult to distinguish between the same twins. Very high.
What if someone stole my face
Disadvantages of face recognition
Face recognition is not perfect, it still requires a lot of work to become flawless. For example, the facial recognition function of Samsung's Galaxy Note 8 can be deceived by photos, so the problem of deception system needs to be solved quickly. Because no one wants to end in the next episode of "Game of Thrones." Yes, the show is great, we don't want to be stolen.
Examples of face recognition
FaceID feature of iPhone X
iPhone X can identify its owner. The FaceID function allows you to unlock it just by looking at the phone. The TrueDepth camera system is also possible-there is a small line at the top of the screen. It contains many different sensors that make this technology as accurate as possible:
1. Infrared camera
2. floodlight
3. Front camera
4. Point projector
5. Proximity sensor
6. Ambient light sensor
7. iPhone X FaceID function
This is how it works. iPhone X uses flood illuminators to detect your face. Even in the dark, infrared cameras can take infrared images. Point projectors project on 30,000 invisible infrared points. The infrared images and dot patterns pass through the neural network. Make a push to create a mathematical model of your face. Then, compare it with the model you set up earlier to see if it matches.
To set up FaceID, you just need to follow the instructions given to you by your phone. Therefore, you slowly rotate your head around to let faceID remember your face. Even if you change your hairstyle, you can use it with glasses and a hat.
Finally, statistics show that the chance of another person using their fingerprint to unlock the phone is 1:50,000, and the chance of another person using their face to unlock the phone is 1:1,000,000. As you can see, it is a very effective and safe technique.
KFC payment smile system
KFC has introduced a new way to buy food in China. This is a smile. A new concept store in Hangzhou introduced a "smile payment" system using facial recognition. So how does it work? People must approach the order booth. First, you place an order, click "Pay", and then choose a table in the restaurant. Then look up at the camera to verify your payment, and enter your phone number to complete the transaction.
The machine uses a 3D camera and "motion detection algorithm". These technologies will prevent scammers from simply holding up pictures of others. The goal is to attract young KFC customers.
With thick makeup and different hairstyles, even if you consider these factors and add multiple people in a crowded scene, it can still correctly identify the person.
Google's Clip Camera
This camera is different from any other camera you have used before. It was made by Google, and like everything Google does today, it uses machine learning to do some very special things. With this camera, the computer can decide when to press the shutter button. You just open it, point it at the world, and the computer will determine if something interesting is happening, and then take a picture of it.
Google Clips can recognize your face and that of your family.
It works as follows. You turn it on first, and then pair it with your phone. After pairing, you can place your phone as needed. You rotate the lens on the clip to the "on" position, and a small LED indicator starts to flash to inform you that the lens is open and you are looking for something to record. The idea is that you just need to put it down or trim it into something, and then let it do it. It looks for content that the Google algorithm thinks may be interesting, and then records a 7-second snippet of that content. It may be that your child is playing or someone is smiling just right. The camera will learn over time. With facial recognition, it can recognize your face, family's face and even pets. Eventually, it learned to take pictures of some people and ignore others. Okay, it sounds super creepy. But don’t worry! All data is stored only on this camera, is fully encrypted, and can only be transferred to the phone paired with it. And all facial recognition only happens on the device.
Therefore, Google Clips has become an extraordinary example of facial recognition implementation.
Facebook's DeepFace
The Facebook research team has created a deep learning facial recognition system called DeepFace. It can take 2D photos of people and create 3D models of faces. Now, this can rotate the face, so you can compare photos taken from different angles or poses. Aging is no longer a problem. It is possible to create a "face fingerprint" system from areas of the face and bones with hard tissues (such as the eye sockets or the curved part of the nose or chin), which obviously will not change with age. However, the main reason for the increased accuracy of DeepFace is a computer teaching technique called "deep learning", which uses algorithms to try to determine whether it is on the right track. Every time it matches two faces correctly or incorrectly, it remembers the steps taken to create the road map, and the more times this process is repeated, the more connections appear on its map, and the task becomes The more accurate. The idea is to let the computer build a network of connections, just like our neural network of interconnected neurons.
Facebook's DeepFace algorithm
Facebook's neural network has 20 million connections, and every time a photo is uploaded and tagged, the connection keeps increasing. The larger the data set, the better the computer performance. Facebook’s advantage is that the data needed to train the computer to recognize faces already exists on the platform in the form of a library of 4.4 million tagged faces.
Facebook's DeepFace statistics
in conclusion
I hope this article can be enlightened on the subject of facial recognition. Now that you understand how this technology works, you can now come up with ideas on how to apply it to your specific business or project. Face recognition is a fast-developing train. It is at the forefront of technological trends, so please book your tickets quickly.
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