Employee Surveillance System Using Face Recognition

Abstract

Advancement in technology has made face recognition system more prevalent and convenient to identify a person without a manual system which contributes to time consumption. In this system, facial recognition is by the means by which the employees are monitored. Our project addresses the problems present with manual surveillance by automating it in an efficient manner. Machine learning and deep learning have benefited people from all walks of life, and we plan to use machine learning in our surveillance system to build this specific project with the aid of Python and its comprehensive modules. The project involves a real-time detection of faces which are then matched with the corresponding face in the database. An excel sheet stores the time at which the login has taken place when the detection occurs. To achieve the goals, we used a combination of machine learning techniques and various logic-based algorithms.