AI
Face Recognition Attendance System
Camera-based attendance with reports.
Project overview
Face Recognition Attendance System is a mentor-guided AI project designed for university submission. AI attendance using face embeddings, classroom capture, duplicate checks, and exportable attendance sheets. The build uses Python, OpenCV, Flask, SQLite and is structured so you can explain architecture, modules, and test cases during viva. Typical delivery timeline is 6–8 weeks depending on package and college deadlines.
Best suited for: CSE / AI&DS students focusing on computer vision or NLP applications
Tech stack
Objectives
- Design and implement a working solution for “Face Recognition Attendance System” aligned to academic evaluation criteria.
- Demonstrate core features such as Face enroll, Live capture, Reports.
- Produce documentation (synopsis, report chapters, and PPT) suitable for guide approval.
- Prepare viva-ready explanations for design choices, tech stack, and future enhancements.
Key modules
- Module: Face enroll
- Module: Live capture
- Module: Reports
- Documentation, deployment notes, and viva Q&A
Key features
- Face enroll
- Live capture
- Reports
- Admin panel
Deliverables
- Source code
- Model notes
- Report
- PPT
- Demo video
Learning outcomes
- Runnable source code with setup guide
- University-style report draft
- Presentation deck (PPT)
- Mentor review checkpoints
