How to integrate face recognition into your mobile app?

Face recognition is changing the mobile app landscape by offering a secure and convenient way to interact with devices.

Users can unlock smartphones, authorize financial transactions, and personalize their experience more easily than with traditional methods like passwords and PINs.

The global face recognition market, valued at $6.3 billion in 2023, is projected to grow to $13.4 billion by 2028, reflecting an annual growth rate of 16.3%.

This trend is evident in mobile apps, where 72% of users prefer face biometrics over passwords, contributing to the mobile biometrics market's anticipated expansion to $184.8 billion by 2031.

Face recognition technology is driven by four core steps: face detection, face alignment, template extraction, and face matching. Let's explore how they work together.

Face Detection
Face detection finds and marks human faces in images or videos by drawing bounding boxes around them. Modern face recognition systems use AI and machine learning (like Convolutional Neural Networks) to detect faces even in tough conditions such as bad lighting or different angles.

Face Alignment
After detection, the face is adjusted to a standard frontal position by using key facial landmarks (eyes, nose, mouth) to correct scale, rotation, and perspective differences. This makes the face look consistent for better accuracy in later steps.

Biometric Template Extraction
Template extraction converts the aligned face into a mathematical model that captures its unique features, such as shapes, textures, and patterns.
Advanced algorithms create a digital code that represents the face, allowing easy comparison with other templates.

Face Matching (1:1 and 1:N)

• 1:1 Face Matching (Face verification) compares the face template with one reference template to confirm identity, like unlocking a phone.
• 1:N Face Matching (Face identification) compares the face template with many others in a database to identify someone, often used in security and surveillance to find people in a crowd.

Face recognition improves security in mobile apps with seamless identity verification and authentication. Here are some examples:

• Unlocking Devices: Use face recognition software to unlock smartphones and tablets quickly and securely, instead of using passwords or PINs.

• Authorizing Financial Transactions: Add an extra security step by requiring face verification before completing payments or transfers.

• Enhanced Login Security: Add a layer of security as a secondary authentication factor along with passwords, creating a multi-layered defense.

• KYC (Know Your Customer) Compliance: Face recognition technology plays a critical role in KYC processes by verifying the identity of users during registration or onboarding. This helps companies meet regulatory requirements, prevent fraud, and ensure that users are who they claim to be.

With face recognition software the app can adjust personalization based on the first selfie taken during the initial setup. Here’s how it works in different scenarios:

• Personalized Content Recommendations: Streaming apps use face recognition to suggest movies or shows based on the user’s preferences.

• Adaptive User Interfaces: Apps can change their look and features based on who’s using them. For example, a news app might show customized articles, or a fitness app could suggest personalized workout plans.

• Contextual Features: Social media apps can automatically tag users in photos or videos, making it easier to share content without manual tagging.

• Targeted Offers: Retail and e-commerce apps can recognize returning customers and offer personalized promotions and product recommendations based on their past activity.

Native Face Recognition API
Face recognition APIs provided directly by the device’s operating system (OS), such as iOS or Android. These APIs are built into the operating system, so developers can add face recognition to their apps.

Examples:

• Apple’s Face ID (part of iOS)
• Android’s Face Authentication API (part of the BiometricPrompt framework)

Open-Source Face Recognition SDK / API
Publicly available software components for face recognition, with source code that can be freely viewed, modified, and shared.

Examples:

• 3DiVi Open-Source Face SDK
• OpenCV
• Dlib

Commercial Face Recognition SDK / API
Face recognition SDKs/APIs from third-party companies, available as paid products with licensing agreements.

Examples:

• 3DiVi Face SDK
• 3DiVi Omni Platform
• Microsoft Azure Face API
• Amazon Rekognition

Technical Requirements
Make sure the face recognition technology you choose works with your app's programming languages, hardware, and operating systems. Here’s how to approach it:

Programming Languages Compatibility
Choose an SDK / API with Java, Kotlin, Flutter, or Swift support or wrappers.

Hardware Specifications

• Cameras: Check that the face recognition technology works with your camera hardware. Higher resolution cameras improve accuracy.
• Processing Power: Ensure that the device can handle real-time face recognition.

Operating System Compatibility

• iOS: Confirm support for the iOS versions you target.
• Android: Check compatibility with various Android versions and devices.
• Cross-Platform: Choose a technology that works on both iOS and Android.

Data Storage and Security
Here’s how to address data storage and security:

Encryption:

• Data at Rest: Encrypt facial data stored on devices or servers using strong encryption algorithms such as AES (Advanced Encryption Standard).
• Data in Transit: Use secure communication protocols (e.g., HTTPS) to encrypt data transmitted between the app and server.

Secure Storage:

• Local Storage: Use platform-specific secure storage (e.g., Keychain for iOS, Keystore for Android).
• Server Storage: For server-side storage, implement access controls and regularly audit security practices.

Compliance with Regulations
Adhering to data privacy laws is essential for lawful use of face recognition technology. Here’s how to ensure compliance:

GDPR (General Data Protection Regulation)

• User Consent: Obtain explicit consent from users before collecting and processing their facial data. Implement mechanisms for users to easily provide or withdraw consent.
• Data Protection Impact Assessments (DPIAs): Conduct DPIAs to assess the risks associated with processing facial data and take steps to mitigate them.

CCPA (California Consumer Privacy Act)

• Consumer Rights: Allow users to access, delete, or manage their data. Implement features in your app that allow users to manage their data preferences and requests.
• Transparency: Inform users about data usage and privacy policies.

1. Define your goal, technical requirements, and use case —authentication, user identification, emotion detection, etc.
2. Choose the right solution: Pick between an SDK or API and decide if you want a native, open-source, or commercial option.
3. Set up your development environment:

• For iOS: Install Xcode, set up your project with Swift or Objective-C, and use CocoaPods or Swift Package Manager to add libraries.
• For Android: Use Android Studio with Java or Kotlin and integrate an SDK or API using Gradle.

4.Integrate face recognition SDK/API

• SDK: Add dependencies, set up the SDK, and configure face recognition features in your app.
• API: Get API keys and make HTTP requests to integrate with the API endpoints.

5.Testing and error handling

• Test under different conditions (poor lighting, various angles, obstructions).
• Manage errors (e.g., no face detected, multiple faces detected, recognition failure, etc.) with clear prompts, guiding users on what to do (e.g., “Position your face within the frame”).

3DiVi offers solutions that streamline the development process and ensure successful integration into mobile apps. Here's how we can help:

Face recognition SDK and API
Our tools work with C++, Java, Kotlin, Swift, and Flutter on both Android and iOS, offering high accuracy and performance, ensuring easy integration, top-rated accuracy in NIST tests, and high performance.

Expertise and Support
Our team provides help from setup to ongoing maintenance, making sure your app runs smoothly.

Customizable Solutions
Whether you need a simple setup or a custom solution, 3DiVi offers flexible options to fit your needs.

Data Security
3DiVi keeps your facial data safe with strong security measures and follows privacy rules like GDPR and CCPA.

Ready to integrate face recognition technology into your app? Contact 3DiVi today to discuss your project and see how our expertise and solutions can turn your vision into reality.