How to Build a Face Recognition App: Essence, Benefits, Working Algorithms, and More

Facial recognition as one of the Artificial Intelligence (AI) trends is no more an extraordinary thing. According to the statistics collected by Pew Research, more than 80% of Americans use this technology, apply to facial recognition software development, or at least know what it is. According to CSIS data, the accuracy of facial recognition platforms can reach 99.97%, which makes it an irreplaceable instrument to use in various spheres of humans’ lives, like the following ones:

• Law enforcement. Facial recognition is helpful in preventing public threats in crowded places (e.g., airports, train stations, underground, etc.).
• Fleet management. The use of technology can assist entrepreneurs in avoiding the theft danger of their vehicles.
• Home security. Face recognition app is a reliable helper in house protection identifying whether strangers come into the house through the detection systems.
• Border protection. Border controls can easier detect and obstruct border crossings by known criminals and suspects.
• Ridesharing business. Business owners from this business sphere often build a face recognition app and use it to ensure that the driver picks up the right passenger.

We’ve enlisted only some of the most common examples to show you how in-demand facial recognition technology is on the market. So, its profit is projected to grow by Statista from about 5 billion dollars in 2021 to more than 12 billion dollars in 2028. Moreover, this technology is quite popular: the researchers say that 7 of 10 governments in the world widely use facial recognition innovation and think about how to build a face recognition app.

The above-gathered statistical data prove that government services and various businesses frequently ask themselves about how to make facial recognition software and successfully utilize it.

Now we’ll dive deeper into what facial recognition technology is and how it actually works. You’ll also get to know the ways FRT is performed and the steps to pass when identifying faces, which is essential to understand before you start thinking out how to build a face recognition system.

However, considering the below information, you need to remember that software with complex processes like facial recognition should have a customer-friendly interface, that'll be easy to navigate.

Face recognition is a technology with only one main goal - to recognize people's faces. Using a smartphone camera the program checks multiple features of a person's face. When you create facial recognition software, you should know that there are more than 80 metrics that have to be tracked, memorized, and stored in such an innovation-based app’s database to compare them with a face when it's needed.

The facial recognition software measures structure of a person's face, like the distance between eyes, size and position of a mouth, edges of a jaw, width of a nose and many more. Moreover, it recognizes such parameters as the user’s sex, emotional state, or even age approximately. All this data creates a so-called faceprint stored in the memory.

The most common ways to recognize humans faces are the following:

• 2D and 3D recognition
• Identification of a face in a controlled background
• Face recognition by the skin texture
• Face search based on color
• Face identification via thermal imaging camera, etc.

How to create facial recognition software and make it work for company needs? To gain these purposes, you should have a camera, perfect recognition and comparison algorithm to use, and a powerful server for your collected data storage.

But before giving this process a proper embodiment, you should clearly realize the operating mechanism of the FRT-based software.

The overall process of face recognition takes four stages. At first, the program captures the image of a face. Then, it extracts the needed data from the image. During the third stage, the program compares extracted patterns with the ones stored in the database. And during the final stage, the machine decides whether the pattern matches or not.

Let’s deepen the mentioned stages, revealing more details as to how the face identification process is passed.

First off, the face should be found. This is not about recognizing a particular person, but just a picture of somebody’s face — through a camera of your smartphone, as a photo from its memory, and so on.

Identifying face references after that, the algorithms perform much more complicated work than earlier searching for the facial features that’ll be able to identify the individual person’s characteristics.

The face can be improved then, which is necessary to simplify the object-matching process. After the frontal image is obtained, the facial recognition system comes to the next stage of its working flow.

A digital portrait of the person’s face is created to perform further comparisons with images located in your database. This portrait doesn’t include criteria like hairstyle or age.

Finally, the recognition process is over, and the match from the database is found and shown to the user who requested it.

Such a complex flow as facial recognition technology facilitates the lives of different specialists day by day. That’s why it obtains a lot of supporters who search for how to create a face recognition app customized for particular business needs or find some great ready-made examples of its application.

If you really want to create an app for Android or iOS with the facial recognition feature, you will need to see how others handled this task first. That's why we've prepared the best facial recognition apps which can be a great example for you. Let's examine them.

FaceLock is free facial recognition software for Android. The main area where face recognition is applied is security. FaceLock was one of the very first apps who used it. The idea of the app is to secure some apps and confidential files with the lock which only you can unlock. With your face, of course. The app has a simple interface which can be easily customized according to a user's needs. There is a free and paid version of extended functionality.

The MojiPop app was created by Eureka Studios. On both the Android and iOS operating systems, it is free to use. Planning how to build facial recognition software interesting for users, Eureka provided them with a variety of animated stickers that can be changed according to FRT. The app's architecture is quite straightforward, with basic navigation and an interactive keyboard that keeps users interested.

Applock is one of the greatest face recognition apps for Android. In terms of security, it is difficult to surpass. To protect your personal information, it can restrict access for others. You can safeguard your personal information, account details, and other applications. Applock supports voice and facial recognition, which makes it simple to access your mobile device.

FindFace is an Android face recognition app. It offers a user to upload a photo of a stranger and find his or her in social networks. The app is only for fun; however, it doesn't mean that it works with mediocre efficiency. The developers of this facial recognition search app used AI technologies which helped them to reach 95% of accuracy and check 250 mln faces in less than half a second. Moreover, the startup released a cross-platform API that can be used in mobile and web apps.

Facial Metrics Analysis Pro is an Android FRT app example and another interesting idea of how to develop facial recognition software for entertainment. If people often tell you that you look familiar to them, you should try Facial Metrics Analysis Pro. The app analyzes your facial metrics and shows a celebrity you most resemble.

FaceFirst is the next FRT-based application you should pay attention to. As a tool for recognizing people from a distance, FaceFirst is primarily employed by law enforcement and transportation hubs. The database of the system makes facial recognition simple. Real-time notifications and emails are also included.

LuxandFaceRecognition is an Apple face recognition app. It is used for people identification. All you need to do is to tap on a face and give it a name. The program memorizes it and then can identify people it already knows. The app itself isn't exciting because it has inferior functionality. However, its developers offer an SDK that can be used in more sophisticated projects.

Face2Gene is a medical face detection app that you won't find in usual app stores. The app developers claim that it can identify various genetic disorders. It works this way, a program compares a photo of a person with multiple images of people with different syndromes and searches for similarities. Thus, it can identify diseases faster than in a lab.

Before you start thinking of how to make a face recognition app for your business, let's discuss the bright and dark sides of face recognition systems. It will help you weigh the pros and cons of FRT implementation and see how effectively it can be used for your business.

We’ll start with the most popular advantages of why you should develop face recognition app and how it can enhance your business.

Contactless identification

If you decide on how to make face recognition application to identify your company staff or people in a crowded place, this FRT opportunity can be beneficial for you as it’s much faster than ordinary fingerprint scanners. Moreover, in case you have a company of more than 100 employees, face recognition systems will be even healthier than the fingerprint detectors

Recognition speed

The FRT technology isn't new, which means it works much more efficiently and faster than a few years ago. So, it takes very little time to identify a specific person if their metrics are in a database.

Enhanced security

We are talking not only about users' private information security. Facial recognition technology can be used in crowded public areas like stadiums, hospitals, railway stations, shopping malls, etc. The system easily differentiates staff from visitors who come to a restricted zone without special permission. Moreover, by answering the question of how to create face recognition system, you’ll improve security levels in any place with valuable goods.

Verification automation

It means you can save resources earlier needed to hire additional personnel. Furthermore, the FRT system will tirelessly work day and night, allowing you to concentrate on other business tasks.

High accuracy

A machine pays attention to the facial structure, and it is much more difficult to fool it and hide something so that the identification results will be as precise as possible. Moreover, the face recognition software development technologies are constantly improving, and cameras are being enhanced daily, which means the accuracy rate will only grow.

Face recognition software has lots of bright sides. Nevertheless, it also has some drawbacks which you need to know about to make a well-considered decision about Face recognition programs application.

Processing difficulties

System work 24/7 requires lots of space to store and many capacities to process. In addition, the pics or video you need to film has to be of the highest quality to recognize faces, meaning it needs large spaces to store them. All these factors increase the cost of a project and require significant investments. So, you should pay attention to them when deciding how to make a face recognition software.

Hair problems

The problem with facial recognition technology is that the system can't recognize people with and without beards and moustaches. If a person wears them all the time, there will be no problem. But if a person one day decides to shave his beard, the system will not be able to identify him. As an option, an administration can ask all men not to grow facial hair and often shave it. Otherwise, the face recognition software app can make mistakes.

The Angle issues

If a person looks right into a camera, the accuracy level would be quite high. This number is achieved only with good lightning and right face position. Glasses, bad light, facial hair, hats, and makeup worsen the recognition results. The situation can be improved if the database is constantly updated with the freshest images.

The last but not least point in this discussion is that you should monitor the access to the FRT system and track whether it’s applied by the intended usage. Eric Schmidt says the following concerning this danger:

Nevertheless, you can deal with the said facial recognition application development problems more effectively if you apply to a skilled tech partner for help. They’ll assist you in overcoming the FRT drawbacks and create qualitative software. Now, let's move on and see how we can integrate face recognition technology into your face recognition application.

To consider all the ins and outs of facial recognition solution building, you can contact an outsourcing face recognition software development company skilled in creating products like that. You can come to the provider, only having a raw software concept and needing to discuss your app idea. The vendor’s specialists will help you handle all the other issues.

Let’s follow up on the typical FRT software creation process based on the example of the Cleveroad Software Development Lifecycle (SDLC). So, after you apply to a vendor for a software development collaboration, your request passes the following stages as described below.

This stage means the specialists have clarified with you all the initial questions and requirements about your project. So, it’s time for the Solution Team to proceed with the obtained information as to how to create a facial recognition system. The team (consisting of a Solution Architect, Business Analysts, and a UI/UX designer) identifies the following criteria:

• Company aims
• Concerns and constraints (e.g., privacy issues, scalability problems)
• Project scope (e.g., database creation peculiarities, matching algorithms to use)
• Necessary quality attributes of your future project, etc.

Thanks to the Discovery Phase services, the facial recognition software development company changes the gathered project data into a clear plan required for further actions. Particularly, they mention the platforms to cover, create a detailed feature list for your upcoming FRT application (containing such core functionality as face features template, fast matching, features generalization, etc.). During this stage, the team composition is also defined as well as the detailed project estimation. Moreover, if you require tech consultations regarding the project, the specialists schedule meetings to discuss all the additional issues you are interested in.

Now it’s time for the UI/UX designers to work on the future interface of the face recognition solution. They make face recognition software design concept and a UX map (the designers’ participance is crucial there). Furthermore, they start creating the solution’s upcoming design from wireframes and other essential points to the screen-by-screen interface’s creation, which will be user-friendly and easy to navigate.

After the UI/UX design services are rendered, the developers start encoding the predefined app features. All the development process is divided into several sprints — 2-week periods after which a part of the prepared functionality (or a whole app) can be delivered.

What are the peculiarities that differentiate an FRT-based app development from others? We’ll name some of them for you to consider.

• Answering how to build face recognition system, the developers not only bring the feature list to life. They also build an extensive database with face photos (of about several thousand). The faces in these photos should be pictured from different angles for more recognition accuracy.
• Adding new pictures to the database, they also train the app to identify faces properly. The appropriately built system should clearly define various facial features (e.g., mouth, eyes, nose, etc.)

The QA engineers are thoroughly checking every piece of created functionality to ensure its accuracy. They also verify if the algorithm trained by developers works properly, defining how it recognizes faces in real time. If something goes wrong, the QA team prepares bug reports for the coders to make hotfixes.

After the previous development stages are finished, the QA engineers make final checks to verify the solution’s operating seamlessness. Then, on the release day, the specialists publish the mobile application in the marketplaces (App Store for iOS applications and Google Play for Android solutions). If you’re satisfied with the outcome, the software development staff will hand over the project materials to you.

The cooperation with the software development vendor is not finished after they’ve ended up to make face recognition app for you. The specialists will care about your solution’s timely upgrade, code optimization and bug fixing to help you ensure the quality of your service, and attract more clients.

As we've already mentioned, some companies released their SDKs along with their mobile applications. However, we will compare more popular tools that reach functionality and a higher level of accuracy, helping you find out how to make a facial recognition app which will match your business requirements and satisfy needs.

Microsoft Azure offers an API that you can integrate when create face recognition app. The tool provides such features as face detection, face recognition and even emotion recognition, defines age and gender, can support multi-face tracking. However, the significant disadvantage is that the service can work only with images not with videos. Moreover, the company doesn't offer SDK for developers.

OpenCV is an open-source library for image processing, which will be helpful for you when deciding on how to create face recognition software. With the help of this library, you can detect faces, process videos, and track more than one face. The system offers you an SDK. Nevertheless, it also has some weaknesses. The tool can’t recognize faces on images, doesn't define age, gender or ethnicity, and there is no API at your convenience.

InsightFace is an open-source Python library dealing with RetinaFace - the trustworthy modern face identification system. Such a repository stays quite active these days. Face recognition accuracy with InsightFace is about 99,86%.

Amazon provides you with an API. With its help you’ll be able to answer how to create a face recognition software detecting faces, recognizing faces on images, and defining the age and gender of a person. There is also no SDK for devs .

DeepFace is a Python face recognition library which contains AI face recognition models and allows to handle all FRT tasks automatically in the background. Additionally, this library provides other face identification algorithms as FaceNet and InsightFace. A REST API is available, but it only allows check methods, making it impossible to form face collections and locate your face within them.

Find Face is a cloud API that is needed to process images. It also can detect faces, verify it (compare faces on several images), identify a face, define age, gender, and emotions.

DeepVision is an AI-based mechanism allowing to identify not only faces but also gender and estimate the age of the pictured people. However, their site doesn’t contain any detailed information as to the programming languages they have a match with or payment models, and it can mean that they collaborate with enterprise-level businesses.

Kairos is one of the very few companies which offer SDK and an API. This software solution is able to detect faces, work both with images and videos and define age, gender, ethnicity and emotions. There are many more tools and instrument which you can try. Some of them offer a free trial period so you don't even have to pay at first. These tools are all great; the outsourcing vendor will help you choose the best one while deciding how to develop face recognition software.

Facial recognition technology is growing in popularity, making people’s lives easier in different spheres of their activity. However, its development is not that easy as it sounds: only creating a facial recognition app is not enough for its proper functioning. It’s also required to train this AI-based software organism to identify faces from a large database. So, you need a trustworthy tech partner that will consult you on how to make facial recognition software helpful for your business to grow.

Cleveroad is eager and capable to assist you with such a solution creation. We are a CEE-based outsourcing software development company providing businesses of different sizes with digital products boosting their company performance and increasing profit.

Cooperating with us, you’ll get the following:

• A powerful facial recognition app fully fitting your particular business needs and responding the latest safety and security standards
• Non-Disclosure Agreement (NDA) signing per your request to protect your software concept’s uniqueness
• Reliable protection of your data with our Firewall as a Service: web attacks and intrusions will be duly prevented
• A fast software development process with no bureaucracy or hidden costs
• A team of qualified professionals capable to adapt to all the business schedule changes and matching all the requirements
• Innovative tech stack and cutting-edge software creation approaches
• A team of QA engineers thoroughly checking your app functionality at each of the development stages and ensuring its security, etc.

Having a tech partnership with a skilled outsourcing software development provider like us is your key to business success. Let’s start your beneficial cooperation with our company that will change your business for the better!