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Realtime Face Attendance System using Machine Learning

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A Realtime face attendance system using Haar Cascade frontal face is a Machine Learning application that uses Haar Cascade classifier algorithm to detect and recognize human faces in real time. The system captures live video feed from a camera, and applies the Haar Cascade classifier to detect the presence of a frontal face in the video frames. The detected face is then compared with a database of registered faces to mark attendance. The system can be used for attendance tracking in various settings such as schools, workplaces, and events. The advantage of using Haar Cascade algorithm is its high accuracy in detecting frontal faces, making it an ideal choice for this application.

#facerecognition #HaarCascade #attendanceautomation #machinelearning #biometrictechnology #innovation #digitaltransformation.

What you will get with this project?

  1. Complete Source Code
  2. Installation Video (Step by step)
  3. Code explanation (Overview)
  4. Project Report
  5. Power Point Presentation

Customers reviews

5 Reviews Write a review
  1. Maithili Pande

    This project works as it is. Project report is excellent. I will add my own images in that before submitting it to university.

  2. Priyank Sharma

    Machine learning model is not bad. If I am showing my face using image, it doesn’t marking the attendance. I liked the code explanation video. Thanks Ma’am

  3. Sahil Bajwa

    This project is a game-changer for universities and schools. It not only simplifies the attendance-taking process but also enhances security by preventing proxy attendance. I would highly recommend this project as mini or final year project.

  4. Jitesh Patel

    Thanks for the code explanation video and project installation video. you saved my final year semester! for sure I will get 100/100.

  5. Jenny

    Awesome project. Works well !

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