24 best Java Face Recognition libraries in 2024

Java face recognition libraries provide components to build AI systems with face detection and recognition. It detects faces, gender, biometrics, and more.

In the fields of augmented reality and artificial intelligence, you can use such an open-source library that implements face recognition technology into your application. This technology can be applied to prevent crimes, unlock phones, execute smart advertising, find missing people, ensure law enforcement, aid forensics, and so on. OpenCV is an open-source computer vision library with several modules for object detection, face recognition, and augmented reality. The flexibility and scalability of Java, combined with the applications of AI systems, can build recognition software with ease and finesse. 

Below are our picks of the 24 best Java face recognition libraries that are open-source in 2021. You can use components from these libraries to build AI software and implement face recognition features in your application. FaceDetector is a face recognition library for Android apps that also works perfectly with Fotoapparat. It can be used with any camera library or source of your choice. On the other hand, Fast-face-Android is an Android app for real-time face landmark detection. It lets you check landmarks in 60ms and works with a HOG detector. FaceRecognition, on the other hand, helps you implement face detection using PCA, LDA, and LPP in Java through the K-nearest neighbor classification algorithm. These libraries have different features that can enhance your project and suit your requirements.

mlkit:  

• It is a mobile SDK provided by Google. It brings machine learning capabilities to Android and iOS apps.   
• It provides cloud-based services, allowing for more powerful and dynamic face recognition capabilities.  
• ML Kit optimizes performance on mobile devices.  

FaceDetector:  

• It plays a major role in identifying and locating faces within images.  
• It enables the extraction of facial features. It needs features like face recognition, emotion detection, and analyzing facial expressions.  
• These libraries can detect and analyze human faces in different applications.  

PicassoFaceDetectionTransformation:  

• PicassoFaceDetectionTransformation is a Java library.  
• It is a Java library used in Artificial Intelligence, Computer Vision applications.  
• This Android image library saves memory by cropping images above Face Detection. 

FaceRecognitionApp:  

• It can control who gets into sensitive areas or systems so only authorized people can enter.  
• It is a safe way for users to prove who they are instead of using passwords or PINs.  
• Integrating face recognition in applications automates processes, reducing the need for manual verification.  

fast-face-android:  

• It is a tool designed for efficient face recognition on Android platforms.  
• It is crucial for applications that need real-time processing. The process is such as surveillance systems or user authentication.  
• Security-related apps must ensure that unauthorized people cannot access them.  

GlideFaceDetectionTransformation:  

• It is a Java library used in Artificial Intelligence, Computer Vision applications.  
• Glide is an Android library that transforms images. It saves memory by cropping around faces.  
• It can be valuable for apps that involve working with images containing faces. Those are such as social media apps or photo editing tools.  

Android-Face-Recognition-with-Deep-Learning-Library:  

• It refers to a specific library for face recognition using deep learning in Java for Android.  
• It is often used for security purposes. Those purposes are such as unlocking devices or accessing sensitive information.  
• Use this to personalize user experiences within applications. 

Android-Face-Recognition-with-Deep-Learning-Test-Framework:  

• The "Android-Face-Recognition-with-Deep-Learning-Test-Framework" in Java can be significant for face recognition libraries.  
• It helps test how well face recognition models work in different situations.  
• It helps improve how face recognition works on Android devices.

face-landmark-android:  

• To recognize faces, we need to find and locate specific points on the face in pictures.  
• These landmarks are specific points on a face, such as eyes, nose, and mouth corners.  
• It improves the abilities of face recognition apps made with Java programming language.  

Cognitive-Face-Android:  

• It is a Java library for face recognition. It provides tools to integrate facial recognition capabilities into Android applications.  
• To enhance security, Android apps verify users' distinct facial features for identification.  
• Applications using face recognition can personalize user experiences based on detected facial features.

hms-ml-demo:  

• It helps with Artificial Intelligence, Computer Vision, Deep Learning, Tensorflow applications.  
• This project includes apps developed based on HUAWEI ML Kit.  
• It provides an example of integrating Huawei ML Kit service into applications.  

FaceRecognition:  

• It is significant for various apps. It includes security systems, user authentication, and personalized user experiences.  
• It enhances security by providing a biometric authentication method.  
• Applications can use face recognition to personalize user experiences.  

marvel:  

• It is a Java library used in AI, Computer Vision, and OpenCV applications.  
• It is an open-source Android application that does face recognition using OpenCV.  
• It helps with attendance marking in college. Marvel also assists with any generic use case of face recognition.  

FaceDetectCamera:  

• It is crucial for capturing real-time video or images from the device's camera to detect faces.  
• Developers can integrate face recognition capabilities into their Java apps. It allows to perform dynamic and interactive face detection.  
• It plays a role in connecting the face recognition algorithm with the device's camera. 

boo:  

• boo is a Java face recognition library.  
• Boo is an Android Experiment. Cute little creatures crowd the screen.  
• A face detection algorithm determines if the creatures are being watched.   

MTCNN4Android:  

• It is an implementation of the MTCNN algorithm for face detection on Android devices.  
• It provides an efficient and accurate way to detect faces in images or video streams.  
• It helps in handling face localization, alignment, and scaling. These are essential for robust face recognition in Java applications on Android.

LookAtMe:  

• LookAtMe is a Java face recognition library.  
• It helps in Artificial Intelligence, Computer Vision, OpenCV applications.  
• LookAtMe has no bugs, it has built files available, it has a Permissive License, and it has low support. You can download it from GitHub.  

react-native-facerecognition:  

• react-native-facerecognition is a Java face recognition library.  
• It helps in Artificial Intelligence, Computer Vision, and OpenCV applications.  
• It helps in face detection and recognition.

awesome-ai-services:  

• It is a Java library used in AI, Speech, and Deep Learning applications.  
• It plays a crucial role in this library by enhancing its capabilities.  
• These services often provide pre-trained models and APIs. You can integrate those models and APIs into Java apps.  

react-native-facerecognition:  

• It is a React Native module for incorporating face recognition into mobile applications.  
• These libraries provide face recognition capabilities for Java applications.  
• It allows you to integrate facial recognition features into your projects in Java.  

Android-MobileFaceNet-MTCNN-FaceAntiSpoofing:  

• Android-MobileFaceNet-MTCNN-FaceAntiSpoofing represents a comprehensive set of components for robust face recognition on Android.  
• This component is likely a deep learning model. It optimizes face recognition for mobile devices. 
• It is a face detection algorithm known for its ability to detect faces in images with varying scales.  

TrackEyes:  

• TrackEyes is a Java face recognition library.  
• It helps in Artificial Intelligence, Computer Vision, Tensorflow, OpenCV applications.  
• It is a simple Android tracking and detection app.  

AndroidFaceRecognizer:  

• It is a Java library used in Mobile, Android, OpenCV applications.  
• This is a face detection and recognition app on Android based on Android OpenCV Android SDK.  
• It includes Java and NDK features. You can install an application from Google Play.  

face-detection:  

• It is a Java library used in User Interface, OpenCV, JavaFX applications.  
• It plays a crucial role in Java face recognition libraries. It serves as the initial step in identifying and analyzing faces within an image or video stream.  
• It allows the system to locate and extract facial features. It provides essential data for later face recognition tasks.  

FAQ

1. What is a Java face recognition library?  

A Java face recognition library is a set of tools and algorithms. It enables developers to integrate facial recognition capabilities into their Java applications.  

2. How do face recognition libraries work?  

These libraries use computer vision algorithms. It analyzes and identifies facial features, creating a unique template for each face. The templates are then compared to recognize or verify individuals.  

3. Are Java face recognition libraries open source?  

Many Java face recognition libraries are open source. It allows us to access and change the source code based on their requirements.  

4. Can I use these libraries for real-time face recognition?  

Yes, some Java face recognition libraries support real-time face detection and recognition. It makes them suitable for applications like video surveillance or live authentication.  

5. What are the key features when choosing a Java face recognition library?  

Look for accuracy, speed, and ease of integration. It supports different platforms and the licensing model.