Face Recognition in Android with Images and Videos, Build Security and Attendance Systems in Android | Java and Kotlin
Welcome to an exhilarating journey of mastering Face Recognition and Face Detection Models in Android with Java and Kotlin! This comprehensive course empowers you to seamlessly integrate facial recognition & detection into your Android apps, harnessing the power of both images and live camera footage.
What you’ll learn
- Use of Face Recognition models with images and live camera footage in Android.
- Build Face Recognition & Detection based Security & Attendance Systems In Android with both Java & Kotlin.
- Build Face Recognition Based Android Applications without Any Paid Facial Recognition Service.
- Use of FaceNet and Mobile FaceNet models in Android with both Java & Kotlin.
- Use of Tensorflow Lite models in Android for Performing On-Device Face Recognition.
- Learn to Store Faces in Database for Registration in Android with both Java & Kotlin.
- Use of Google ML Kit library in Android for Face Detection.
Course Content
- Introduction –> 2 lectures • 11min.
- Choosing or Capturing Images in Android –> 7 lectures • 44min.
- Face Detection With Images in Android –> 7 lectures • 48min.
- Face Recognition With Images In Android –> 13 lectures • 1hr 33min.
- Using Tensorflow Lite Models in Android for Face Recognition –> 3 lectures • 16min.
- Storing Registered Faces In Database in Android –> 5 lectures • 26min.
- Realtime Face Recognition: Displaying Live camera footage in Android –> 5 lectures • 35min.
- Realtime Face Recognition: Register and Recognize Faces in Android –> 9 lectures • 44min.
- Storing Registered Faces In Database in Realtime Face Recognition Android –> 3 lectures • 12min.
Requirements
Welcome to an exhilarating journey of mastering Face Recognition and Face Detection Models in Android with Java and Kotlin! This comprehensive course empowers you to seamlessly integrate facial recognition & detection into your Android apps, harnessing the power of both images and live camera footage.
Face recognition has become a pivotal technology used across various industries:
– Security agencies employ it for identifying and tracking criminals.
– Companies utilize it to monitor employee activities.
– Educational institutions leverage it for streamlined attendance tracking.
In this course, you’ll acquire the skills to integrate diverse face recognition models into Android App Development, enabling you to create intelligent and robust applications for Android
Course Highlights:
Understanding the Basics:
Embark on your journey by grasping the fundamental principles behind face recognition models. Explore the two core components of a face recognition system:
1. **Face Registration:**
– Learn to register faces through image scans or live camera footage in Android.
– Capture and store faces along with user-assigned names in a database in Android.
2. **Face Recognition:**
– Dive into the process of recognizing registered faces in android ( Java / Kotlin ).
– Utilize face recognition models to compare scanned faces with registered ones
Image Handling in Android:
Discover essential techniques for handling images in Android, including:
– Choosing Images from Gallery in Android
– Capturing Images using Camera in Android
These skills are crucial for passing images to face recognition models within your Android application.
Face Recognition With Images in Android:
Build your first face recognition application in Android, allowing users to:
– Register faces
– Recognize faces
Utilize two distinct models for face recognition in Android:
1. FaceNet Model
2. Mobile FaceNet Model
Real-time Face Recognition:
Advance to real-time face recognition Android applications, registering and recognizing faces using live camera footage frames. Learn to:
– Display live camera footage in Android ( Java / Kotlin )
– Process frames one by one with face recognition models in Android ( Java / Kotlin )
– Achieve real-time recognition and registration in Android ( Java / Kotlin )
TensorFlow Lite Integration:
Master the integration of face recognition models in Android ( Java / Kotlin ) using TensorFlow Lite. Explore why TensorFlow Lite is the ideal format for implementing machine learning models in mobile applications.
Face Detection:
In face recognition applications before recognizing faces we need to detect faces from images or frames of live camera footage. So for detecting those faces, we are going to use the face detection model of the ML Kit library in Android ( Java / Kotlin ). So in this course, you will also learn to perform face detection in Android ( Java / Kotlin ) with both images & live camera footage.
Course Outcomes:
Upon completion of this course:
– Integrate Face Recognition & Detection models in Android ( Java / Kotlin ) with both Images and live camera footage
– Implement Face Recognition-based authentication in Android ( Java / Kotlin ) Applications
– Construct fully functional Face Recognition-based security and attendance systems in Android ( Java / Kotlin )
In essence, this course serves as a comprehensive guidebook for mastering face recognition in Android app development. Don’t miss out on this opportunity to acquire a skill that truly matters. Join the course now and unlock the potential of Face Recognition in Android!