How to build your own face recognition app

In 2017, the police of Xiangyang (China) placed cameras with facial recognition capabilities near the Changhong bridge. The cameras projected photos and personal data of pedestrians who violated traffic rules onto huge screens for everyone to see. The new attraction was amusing… but only until citizens were mailed their fines.

If you think government and security services are the only ones using facial recognition, think again. This technology is widely applied in everyday life and surrounds us on all sides. EU and UK biometric data protection in airports, smartphone eye scans, Facebook tagging your friends in group photos, and even the face matching apps we are now seeing - all of them are examples of facial recognition technology. Several years ago, you had to spend excessive effort and money to build an app like this, but today it's accessible to everyone.

Smartphones with fingerprint identification no longer surprise anyone. The face identification app is a trend that is still gaining popularity. Even though it's relatively recent tech innovation, it has already been applied in eCommerce and retail, showing increasing success. You can also benefit from a long-term competitive advantage by choosing today to integrate this app into your business solution.

For what is facial recognition used?

Usage of face recognition

Computer vision is one of the most interesting fields of artificial intelligence. The main reason for it's recent attention stems from the desire to automate tasks that otherwise need human interference - surveillance, identification, or access control. As a result, an app that identifies objects, text, actions, and people has appeared. Today, there are even more sectors where these technologies have been applied and are limited only by imagination. Here are several fields that use facial recognition apps:

  • Security. Solutions using face recognition features are popular in this area. Some of the applications include crime and terrorism prevention, skip tracing, visual tracking, biometric identification in airports, driver fatigue assessment, access security, and others.
  • E-commerce and digital banking. There are plenty of applications in retail and digital transactions that help prevent fraud and make online shopping more reliable.
  • Payment solutions. In 2020, Amazon and other e-commerce leaders are expected to release their new versions of payment systems using facial recognition features.
  • Healtcare. The healthcare industry is actively applying this technology to track drug intake, improve the quality of services, and detect genetic diseases showing a 96.6% success rate.
  • Travel and hospitality. Person recognition apps are allowing hotels to reduce check-in time by 40%. The same technology will be applied in almost all fields of traveling soon, from ticket bookings to person identification at resorts.
  • Marketing. One way to increase customer loyalty at hotels, restaurants, and cafes is by using a personal greeting technology. It also helps accelerate service and orders based on previous experience.
  • Smart home systems. The facial recognition feature is a popular part of various smart systems like Smart TV, virtual assistants, and more.

This does not contain the full list, as every industry and entrepreneur can find new interesting ways to use similar solutions for their business development.

Modern trends in face recognition

Facial recognition has been underway since the 1960s but has only developed further within the last several years, thanks to artificial intelligence and IoT. To enhance this technology, artificial neural networks (ANN) are applied. Let's take a look at some modern trends in face recognition.

Deep learning. This is one of the most innovative ways to upgrade face recognition software. Deep learning is based on machine learning algorithms and ANN. The idea of deep learning is to extract a number of individual facial features and traits to make the identification more accurate. This process can be compared to the human brain, which uses large datasets - personal experience. It helps achieve high performance in real-time.

Hybridized solutions. This solution is another modern trend that unites several recognition approaches. It can be a combination of mathematical models, artificial neural networks, genetic algorithms, artificial intelligence, or several types of biometric identification (fingerprint + face, voice + retina.) Hybrid solutions significantly increase the level of recognizing people.

Face finder app. This app is increasingly popular on social networks or dating websites. Based on an uploaded photo, it finds users with similar characteristics and highlights them.

"Pay-by-face" in e-commerce. Chinese payment processing systems are way ahead of the rest of the world. For example, in Hangzhou, a customer can pay at KFC using a facial recognition app. This has been in place since 2018. Today, Amazon and Alibaba are a few steps away from implementing an online payment using face authentication. Sure, this technology won't replace existing means of payment anytime soon, but it will become the next innovative step.

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How to make a facial recognition app

When creating a face identify the app, the most important thing is to choose the right approach before you begin. As a basic option, one can select a ready software model that allows time and money reduction for development. However, in this case, you cannot be sure the system will work flawlessly, there'll be no displacements, and you will be able to add individual features needed for the app.

Another approach is to develop a system from scratch. This choice is for those who want to build an app with unique features and ensure a high level of user data security. Also, it's a great choice in the long run, as it has all the advantages of custom development.

Popular face recognition solutions

The popular face recognition solutions

The market offers ready-made solutions for facial recognition. Let's explore some of the most functional and popular ones together.

Microsoft Azure offers features like photo face recognition, affect recognition, age, and gender identification. For integration, there's an API only, with no SDK for the developers.

Amazon Rekognition also works with images and allows users to identificate person, age, and gender. There's also an API only when integrating.

FindFace was initially available as an Android app, which allowed users to upload a photo on social networks and find an account using the photo's features. Later, the developers created a cross-platform API for mobile apps and face detection websites.

Kairos is one of the few providers that offer both SDK and API. This product allows working with photos and videos to identify faces, gender, age, a person's emotions, and ethnicity.

OpenCV is a library with open-source code and a variety of ready settings for face detection and recognition via photo and video. The system can identify more than one face at a time. The system has only SDK, while API is not available.

Each system has its pros and cons, as well as issues with system learning capabilities, real-time work, etc. Choosing an inappropriate facial recognition solution provider can lead to development problems. Pay close attention to research and market analysis to understand which solution will suit you best.

Facial recognition app with Owlab

Facial recognition app with Owlab

By building a custom facial recognition feature for your app, you'll receive numerous business advantages - from a perfect match for your requirements to endless opportunities for further system improvement. One more important thing, this technology is directly related to user data security, so having your own code with full access is a big plus only custom solutions can provide.

Entrust the development of your facial recognition software app to a team of professionals at Owlab, will give you a product of the highest quality that completely fulfills each required task. You'll also evade the challenges that arise from using a third-party solution, such as:

  • insufficient network learning capabilities
  • inability to identify in real-time
  • low performance under specific conditions like bad lighting or a hairstyle change
  • problems related to memory distribution
  • lack of flexibility for system modification, impossibility to improve or adjust the system
  • operating delays
  • support of particular hardware only
  • usage limitations
  • and more.

Owlab is a credible partner for your business. We build systems for different industries, tailored to individual requirements. At Owlab, we pay special attention to deep learning technology, a high level of accuracy, and security. Our high tech software solutions can identify people, objects, text, and actions on photos and videos in real-time or based upon uploaded files.

By enhancing your service with a custom intellectual face scanner app by Owlab, you can receive a competitive advantage on the markets that require precise identification. You'll also have the opportunity to automate many processes, minimize operational costs and human-related risks, and solve numerous other challenges on the way to successful business development.

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