The technology of facial recognition can improve the customer experience


What do you think would happen if at the mirror and saw another person?

However, even if we alter aspects of our external appearance, such as the shade or the cut of our hair and facial expression when wearing glasses, we still identify ourselves when looking at the mirror. It is because our brains have an inbuilt facial recognition technology that is able to recognize that we're looking at the identical person. We identify ourselves, not by taking a look at our fingerprints, or taking a picture of our iris, but by looking ourselves at the mirror.

Different 'signatures' for the human body are in existence and facial recognition continues to be the most popular biometric method for identification for a variety of reasons, including its convenience and ease of application. It is now incorporated into many areas of life, from the tag of photographs (Google as well as Facebook) and even unlocking your phones (Windows Hello and Apple FaceID) and more sophisticated applications such as those employed by law enforcement officers.

Facial recognition is a software that determines the facial features of an individual mathematically and saves the information as an image. Deep learning algorithms analyze the live or digital image with the faceprint that is stored to determine the identity of an individual. The ideal scenario is one that is in direct view of the camera. However, algorithms are getting better and more efficient with specific advantages for each task. The most sought-after algorithms include Convolutional Neural Networks (CNN), Eigenfaces, Fisherfaces 3D Recognition thermal cameras and many more. Also, image recognition tools for developers, including Amazon Rekognition (part of the Amazon AI suite), and Google Cloud Vision API to integrate face recognition as well as analysis capabilities in an application.

It has brought about a significant change in the method of working for both organizations and companies, but there is one thing that remains the same: people are experiencing (Gartner 2021). Employees and customers alike will be at the center of any company, but using technology to deliver more customized and unique experiences. Biometrics are a great way for brands, organizations as well as retail stores as well as service companies to understand their customers better.

The rapid advancements of AI machines and AI are enhancing the accuracy of facial recognition . There are several industries testing the application of this technology to improve the user experience, more efficient and convenient. Here are some ways organizations and brands are working towards providing customers with a better experience customers:

1. Retail: This segment has been at the forefront of the implementation of the latest advances that are being made in AI, AR and VR technology. Retailers benefit by having checkout-free stores that use face detection and tracking, to help retailers determine where customers spend longer, how satisfied they are when they are at the counter and many other such applications.

2. Enhance loyalty programs for customers: Quick service restaurants can display the history of a customer's orders as well as their favorite meal options as well as pay for their meal, providing an unique interactive experience via their kiosks. CaliBurger Fast-food restaurant chain located in the US has been testing this service in one of their locations. Alipay offers this service to its customers from China.

3. Healthcare-Diagnose ailments: Face recognition can be used to identify conditions that cause noticeable visual changes. Face recognition has assisted in the diagnosis of a rare illness known as DiGeorge syndrome that affects 96 percent of cases. As algorithms become increasingly advanced, facial recognition and medical datasets will be a crucial diagnosis tool in all kinds of diseases.

4. Automotive-Driver Assistance System: In attempt to increase the safety for both passengers and drivers the in-car facial recognition system will monitor the driver for indicators of weakness or fatigue. The facial expressions of a driver can also serve as cues for the driver to alter the temperature, lighting, and entertainment, and provide the driver with a better experience.

5. Hospitality Hotels: Pulling on a profile for a customer who is frequent each time they enter the doorway to show their preferences, enabling the membership plan, or providing personalized greetings are one of the ways that hotels can offer a pleasant experience for guests.

6. Tourism: Some companies are testing using facial recognition in order to identify emotions on a client's face while they browse the booking site. This will provide information on how easy it is to use the website, which offers are popular with clients, what things they are most likely to take part in during vacation or other occasion, and other such. With this information they can provide more customized services to their clients.


What is Facial Recognition work?

The technology of facial recognition is known to a lot of us because of Face ID, which is used to unlock iPhones (however it is not the only use of facial recognition). In general facial recognition does not utilize a massive collection of images to establish the identity of a person, instead it simply detects the person who is the device's sole owner but restricts access to all other users.

Computer vision is utilized to gather data on facial recognition and then process the images using the software for facial recognition. The images are screened digitally to ensure that computers is able to distinguish between a human face an image or statue, or even posters. The patterns as well as similarities within the images are detected using machine learning. The ML algorithm detects facial feature patterns that can be used to identify the face in any photo such as:

  • The face's width to height ratio
  • The appearance of the person
  • The size of each element, for example, the eyes, nose and mouth
  • Unique characteristics

The software for facial recognition, similar to other faces, has various characteristics. In general, every facial recognition software will follow the following process:

1. Facial detection: No matter if the person can be seen in crowds or not, facial recognition can recognize and distinguish an image of a face. Technology advancements have made it easier for software to identify faces even when there's a slight variation in posture, such as either facing the camera or looking away.

2. Analyzing Faces: A image is then analyzed using the image data collection . Face recognition systems are employed to precisely identify distinctive facial characteristics like the distance between eyes, nose length and mouth-to-nose distance and width of the forehead and brow shape as well as other biometrical characteristics.

3. Image conversion: After the recording of a face image, the analog information transforms into digital information in accordance with the individual's biometric characteristics. Since machine learning algorithms are able to only detect numbers, it is essential to transform the face map into an mathematical formula. The faceprint, or the image of the face then gets contrasted with the database of faces.

4. Finding an exact match: Finally, your appearance is compared to many databases of famous faces. The software attempts to match your appearance to those of the database. Name and address of the person will usually be returned along with the image that is matched. If the address isn't available, the data that has been saved is utilized.

Real-life examples of facial recognition

  • Face recognition is utilized by Apple to allow users to unlock their smartphones, sign into apps, and purchase items quickly.
  • Face recognition has been utilized by Coca-Cola in a variety of ways throughout the world. Customers can earn rewards for recycling in certain vending machines in China, personalized ads were dispensed through its vending machines in Australia and for event marketing was implemented in Israel.
  • In 2010 Facebook started using facial recognition technology in the US using their tag suggestions feature to auto-tag users in photographs.

What are the benefits of GTS help you?

It is essential to build the facial recognition algorithm on diverse datasets to allow it to work optimally. Since facial biometrics vary from person to it is essential that the software be able to read and identifying any facial. This is why Global Technology Solutions provide the most high Dataset For Machine Learning that can be used to develop, test and verify models for machine learning.

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