This Flutter application was developed as part of a Graduation Project, focused on modernizing and securing the attendance process using Liveness Face Recognition and Face Detection technologies.
The app uses advanced liveness detection to ensure that a real person is present during the face recognition process — preventing spoofing attempts (e.g., using a photo or video). It's designed for use in both academic and workplace settings, enabling fast and secure attendance logging for:
- 🧑🎓 Students
- 🧑💼 Employees
- 🎯 Liveness Detection — Verifies that the face is real and live
- 🧠 Face Recognition — Identifies users and logs attendance
- ⏱ Instant Attendance — Quick and accurate check-in process
- 📊 User Interface — Clean and intuitive UI built with Flutter
- 🔒 Security First — Prevents spoofing using biometric verification
- Flutter – Cross-platform mobile development
- Dart – Main programming language
- Camera & ML Packages – For face detection and liveness recognition
- The user opens the app and chooses the language for the teacher.
- the student sign up first time only and positions their face within the frame.
- The app performs liveness detection to ensure the person is real.
- Once verified, the app matches the face with registered users.
- Attendance is logged automatically.
- Clone the repository:
git clone https://github.com/Ali-Elsadany/iFace