Invisimark : Seamless Facial Recognition for Attendance
1st Prof. Girish S Shivangudi
2nd Mr. Shrinidhi S Haribhattanavar
3rd Mr. D N Akshay
Department of Computer Science(AIML)
KLS Vishwanathrao Deshpande
Institute of Technology Haliyal, India
gns@klsvdit.edu.in
shrinidhish909@gmail.com
dnakshaya@gmail.com
4th Mr. Shreeram C Machak
Department of Computer Science(AIML) KLS Vishwanathrao Deshpande
Institute of Technology Haliyal, India Shrirammachak77@gmail.com
5th Mr. Nikhil S Salunke
Department of Computer Science(AIML) KLS Vishwanathrao Deshpande
Institute of Technology Haliyal, India nikhilsamsalunke@gmail.com
Abstract--Smart Attendance System for Face Recognition is an easy way to identify students and employees attendance in the class or organization. The Traditional attended mechanism that relies on manual prayer call or biometric attendence system etc are generally laborous procedures prone to error and can be forge by proxy, respectively. This type of system utilizes facial attributes for identification by employing modern computer vision and machine learning methods. It takes live photographs of students, teachers and staff with a camera and uses facial recognition to compare the image to others in an internal school database. Attendance is automatically tracked and stored in a secure, digital file. The objective of the project is to save time, cut down on administrative workload and improve on attendance processing. And it features report generation, trend analysis and can tie in with other management platforms. With its biometric facial recognition technology, this system offers a hands-free hygienic alternative to fingerprint and hand readers (placing the user at a safe distance from the face), and with no hardware required for networking.’CreatedBy using our time clock Software you will be able to shift the focus back on employee productivity by bypassing buddy punching.
Keywords : Face-Recognition, Smart Attendance System, Computer Vision, Machine Learning, Real time Monitoring, Automated Attendance, Image Processing, Deep Learning, Digital Database 1.
