How to Build a Mobile App with Face Recognition Technology?

Between 2020 and 2027, the facial recognition technology market is expected to grow at a CAGR of 14.8%, as per reports. It is one of the fastest-growing biometric technologies as the FRT market is expected to reach $12.92 billion by 2027.

What started as surveillance technology to find criminals and help in border control has now been put forward as a tool to ensure security, increase customer loyalty, entertain users, and do so much more.

But, it is also true that it has always been a topic of debate. While some view it as a threat to social rights others see it as a promising innovation to ease several tasks. Regardless of which group you side with, none can deny that Facial Recognition Technology (FRT) has become increasingly valuable to many industries.

In the Mobile Application Development world, it is being used for retail apps, fleet management apps, security and surveillance apps, and in many other software. If you are also planning to develop facial recognition software or want to integrate FRT into your business mobile app, you have come to the right place.

In this blog, we will discuss everything about Facial Recognition Technology, what it is, the benefits it provides, and how it can be implemented to enhance the experience of your mobile app. So, let’s get started.

Why Is Facial Recognition Technology On the Rise?

It is true to say that facial recognition is one of the most controversial and complex technologies to play with. But, still, the facial recognition startup sector is thriving and not suffering.

Despite controversies, facial recognition startups are flush with VC cash – Techcrunch.

But, what is the reason behind the world going crazy on FRT? Entrepreneurs are finding new ideas every day to develop a solution based on FRT and investors are pouring money. Mobile apps like Jumio and AnyVision announcing new rounds of funding every quarter are the proof.

If you are wondering WHY, we have the answer. Facial recognition technology has applications in every industry and that’s why people all over the world want to try it in order to improve their business processes and develop new innovative solutions.

Also, FRT is evolving significantly due to its growing adoption across several sectors and industries. It empowers a myriad of apps with visual biometric identification abilities. As a result, facial recognition technology is being used for countless purposes, including:

• Biometric identity verification
• The automated checkout process in stores
• Campus security and workforce management
• Customer verification
• Patient identification
• Smart banking
• Improved public security
• Product discoverability by visual search
• Developing targeted marketing campaigns
• Diagnosing genetic disorders
• Store security and fraud prevention
• Running cardless ATM transactions
• Food Image Recognition
• Driving better user engagement on social media

In the last few years, the usage of facial recognition technology has increased a lot. In 2017, Apple released Face ID – the first-ever sign-in feature using FRT. Presently, more than 15-20% of the financial institutions in the USA including banks are using facial recognition to verify documents in order to validate users’ identities.

As per a report from NIST, facial recognition systems and software were found 99% accurate when searching a database to match a picture. Bloomberg also believes that the global FRT market will reach USD 11.62 Billion by 2026, growing at a CAGR of 21%.

Seeing these statistics and market trends, it is clear how substantially FRT technology is expanding. If you are also planning to develop facial recognition software or use it to solve one of your business problems, let’s figure out how you can implement it.

Also Read: Top 5 Artificial Intelligence Tools for Mobile App Development

How to Implement Facial Recognition in Your App or Software?

Before you invest in facial recognition app development, it is essential that you understand the concept completely. What would you like to create and how should it work? Once you have it figured out, here are three ways to implement FRT in your mobile app:

1. Use Native Face Detection APIs

When you develop a mobile app, you develop it for iOS, Android, or both. These platforms offer their own APIs to help you integrate facial recognition features into the app.

Even though the functionality these APIs provide will be limited, you can reduce the cost of face recognition app development by many folds using these options. You just need to integrate the API into your app and ensure reliable picture detection and recognition features.

The most important advantage of using native APIs is that they are optimized for lots of devices and are also improved using hardware acceleration components. For example, Vision API is an API by Apple for things related to computer vision. It has detectors that let you find faces, text, and barcodes.

Native Face Detection APIs
Pros	Cons
Easy to integrate	Lack features
Affordable	Not many options available
Optimized for most devices
Requires no extra time & effort

2. Consider OpenCV Library

This is the commonly used library to develop facial recognition apps. It helps implement computer vision as well as ML in the applications. Basically, OpenCV is an object detection platform that helps detect all types of objects and also works well around several algorithms. This library works well for facial recognition and detection in many cases.

Initially, OpenCV was built for the standardization of the general interface of computer vision and for the invention of new models. Its main advantage is that it is free to use. However, its integration with mobile applications is a bit complex, especially when it comes to face detection in Android. It requires extensive knowledge.

OpenCV (Haar-Cascade)
Pros	Cons
Available free of cost	Unable to detect side faces
Fast and capable of running in real-time (written in C/C++)	Performs poorly in different poses & lighting conditions
Small model size around 400 KB and 10 MB for DLFD	Hard to integrate with mobile apps
Utilizes modern deep learning algorithms	Exists as SDK only

3. Choose a Third-Party Solution

The market is full of various offers to make the development process smooth and highly convenient. You can use third-party services like Microsoft Face API, Google’s Cloud Vision API, Amazon Rekognition, Kairos, and many others to integrate facial recognition in your app or use FTR to improve your business processes. Usually, these services are paid but offer amazing functionality by recognizing not just faces but emotions, ethnicity, and many other things.

Third-Party Solution
Pros	Cons
Advanced capabilities	High cost
High accuracy	Expertise needed
Privacy and support

Each third-party solution will have its own advantages and disadvantages. So, you will have to choose very carefully based on your business requirements and budget. Let’s now take a look at some of the best and most popular APIs to implement FRT in the next section.

4 Best APIs to Implement Facial Recognition in Your Mobile App

Mobile application APIs contribute directly to business growth. So, if you are planning to build facial recognition software or a mobile app, it is best to use an API for implementation. APIs help businesses build innovative solutions while saving costs by increasing the productivity of developers.

Here are some of the best facial recognition APIs:

1. Microsoft Face API

Initially released in 2016, the Microsoft face API is a part of Microsoft’s Cognitive Services. It is built on one of the most advanced facial recognition algorithms ever developed but it still has some limitations. The main features of the API are facial recognition, detection, and emotion recognition.

Using it, your mobile app can detect and identify similar faces while predicting the emotions associated with the face. For example, Uber – a top-notch ride-hailing application, also uses Microsoft’s Cognitive Services to do a real-time ID check of their drivers.

Users simply take a selfie in-app which is then used to find out the driver’s identity by comparing it with the one in the database. Uber protects their driver’s account by doing this check. However, the API has some limitations as well. It doesn’t come as an SDK which limits developers’ flexibility and also doesn’t provide ethnicity detection.

2. Kairos Facial Recognition API

Based on deep learning algorithms, Kairos API provides quick and safe face detection. It is easy to understand, well-documented, and comes with a manual to help you create a good UX for your facial recognition application.

Also, Kairos provides an SDK as well API for facial recognition. Their solution is able to detect faces, work with images as well as videos, and define gender, age, emotions, and ethnicity. As Kairos APIs include cloud-offloading of crucial data, the company offers privacy features and advanced security as well as audits for commercial use.

For integration, you can either use their cloud API or host it on your own servers for maximum control, privacy, and security. Here are some of the features of the Kairos platform:

• Face detection, identification, and verification
• Age and gender detection
• Facial coordinates matching
• Anti-spoof detection
• Diversity Recognition

3. AWS Rekognition API

Amazon Rekognition is based on highly scalable, proven, deep learning technology developed by Amazon’s scientists to analyze billions of images and videos. You will not need expertise in machine learning to use this.

It is an easy-to-use API that can analyze any picture or video fast that is stored in Amazon S3. Always learning new data, Amazon continually adds new labels and features to the service for better facial recognition and comparison.

Amazon Rekognition provides highly accurate facial analysis, face search, and comparison capabilities. You can detect, compare, and analyze faces for several use cases, including cataloging, user verification, public safety, and counting. Some of the common use cases of Amazon Rekognition API are:

• Searchable image and video libraries
• Sentiment and demographic analysis
• Detection of personal protective equipment
• Facial search and unsafe content detection
• Celebrity recognition and text detection

4. Google Cloud Vision API for Face Detection

Being a part of Google’s cloud platform, the Google Cloud Vision API is a fast and reliable solution. But, as of now, it is just available for face detection and not for facial recognition. Cloud Vision offers pre-trained models via the API and the ability to create customized models using the AutoML vision application.

The API lets users understand and analyze the content of an image by integrating ML models in an easy-to-use API. It can help you classify images into several categories, identify text in an image, and detect objects and faces as well. Here is an overview of its features:

• Object and face detection
• Sentiment detection (faces)
• OCR
• Nudity/Violence Detection
• Logo/Landmark Detection

Get Started by Hiring Facial Recognition App Developers at Apptunix

Facial recognition technology or FRT is growing in terms of popularity with every passing day. It is making people’s lives easier with its applications in various industries. However, using this technology is not that easy because of the challenges associated with it.

You can for sure expedite the process of facial recognition app development with the help of tools, platforms, APIs, SDKs, and frameworks but to train the AI-based solution for work the way you want, you will require experienced experts who have worked on such projects.

At Apptunix, we have expertise in developing such applications and software. Also, we are eager to help you in your venture. Our engagement models are highly reliable and flexible and that’s just one advantage of working with us. We can help you build a powerful facial recognition application that fully fits your specific business needs. While working with us, you also get:

• A non-disclosure agreement to protect your idea’s uniqueness
• 100% protection of your confidential data
• 100% transparency with no hidden costs
• Pre-vetted software developers, AI and ML experts
• A team of QA engineers to ensure your app’s quality.

Collaboration with a leading software developer like Apptunix is going to be the key to your project’s success. And, our work doesn’t stop once you launch your application, we believe in long-term partnerships and stand by our clients while providing post-launch support and upgradation services. Get in touch now and start your journey to success.