Student performance is analyzed by their attendance. Nowadays manual attendance is considered as a time consuming job
and one might lose the copy of attendance. So instead of taking it manually we refer to take in biometric, on the whole we want the
total work to be an automated process. For it, to be automated the main goal is to recognize and verify a person's face from the
screenshot captured, because a major part comes with the individual faces and then the information is checked in file along with marks
the attendance for student. Traditional face recognition systems take up a method to identify a face from the given input, but in case the
output is not accurate and sometimes is hazy. In this paper our aim is to deviate from such traditional systems and introduce a new
approach to identify a student using Face Recognition System. There are many techniques which can be executed with it such as Multi
Linear subspace learning using Tensor representation, hidden Markov model etc.
Published In:IJCSN Journal Volume 8, Issue 2
Date of Publication : April 2019
Pages : 172-176
Figures :07
Tables : --
Swapna Munigala :
CSE Department, Osmania University- Stanley college of Engineering and Technology for Women,
Asst Prof CSE Dept, Hyderabad, Telangana 500036, India.
Samiha Mirza :
CSE Department, Osmania University- Stanley college of Engineering and Technology for Women,
B.E IV Year, Hyderabad, Telangana 500036, India.
Zeba Naseem Fathima :
CSE Department, Osmania University- Stanley college of Engineering and Technology for Women,
B.E IV Year, Hyderabad, Telangana 500036, India.
ZubairaMaheen :
CSE Department, Osmania University- Stanley college of Engineering and Technology for Women,
B.E IV Year, Hyderabad, Telangana 500036, India.
Automatic face Detection, Face Identification, Face recognition, Feature Extraction, Face Matching
The system we have developed is successfully able to
accomplish the task of marking the attendance in the
classroom automatically and output obtained is updated
as programmed. On another aspect where we could try
is creating an online database of the attendance and its
self-regulating updates, keeping in mind about the
growth of internet of things.
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