Proceedings ArticleDOI
An automated classroom attendance system using video based face recognition
Anshun Raghuwanshi,Preeti D Swami +1 more
- pp 719-724
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TLDR
In this paper, attendance is registered from a video of students of a class by first performing Face Detection which separates faces from non-faces, and then Face Recognition is carried out which finds the match of the detected face from the face database (collection of student's name and images).Abstract:
This paper proposes and compares the methodologies for an automated attendance system using video-based face recognition. Here input to the system is a video and output is an excel sheet with attendance of the students in the video. Automated attendance system can be implemented using various techniques of biometrics. Face recognition is one of them which does not involve human intervention. In this paper, attendance is registered from a video of students of a class by first performing Face Detection which separates faces from non-faces, and then Face Recognition is carried out which finds the match of the detected face from the face database (collection of student's name and images). If it is a valid match then attendance is registered to an excel sheet. Face recognition is performed and compared on the basis of the accuracy of recognition using Principle Component Analysis (PCA) and Linear Discriminant Analysis (LDA) algorithms.read more
Citations
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An android based course attendance system using face recognition
TL;DR: The experimental result shows that the proposed Android based course attendance system achieved face recognition accuracy of 97.29 by using linear discriminant analysis and only needed 0.000096s to recognize a face image in the server.
Journal ArticleDOI
Biometric-Based Attendance Tracking System for Education Sectors: A Literature Survey on Hardware Requirements
Seng Chun Hoo,Haidi Ibrahim +1 more
TL;DR: This literature survey provides an overview of the types of hardware used in the setting-up of biometric-based attendance systems and places emphasis on the microcontroller platform, biometric sensor, communication channel, database storage, and other components in order to assist future researchers in designing the hardware part ofBiometric- based attendance systems.
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Contactless Attendance Management System using Artificial Intelligence
TL;DR: This attendance monitoring system is proposed using artificial intelligence is designed to improve the students’ engagement time inside the classroom, to communicate to the parents frequently, to avoid proxy attendance and to generate detailed reports for future reference.
Proceedings ArticleDOI
Conceptual Model of the Smart Attendance Monitoring System Using Computer Vision
TL;DR: The conceptual model for a smart attendance monitoring system that uses face recognition to monitor students’ attendance during lectures is proposed and a full view multi-camera structure aimed at effectively capturing and detecting of faces is presented.
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Face Expression Recognition Based on Deep Convolution Network
TL;DR: This paper uses jaffe and ck+ two face expression libraries to verify the algorithm's effectiveness, proves the effectiveness of the algorithm, and shows that its performance is better than the traditional method.
References
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Proceedings ArticleDOI
Video-based face recognition using probabilistic appearance manifolds
TL;DR: A maximum a posteriori formulation is presented for face recognition in test video sequences by integrating the likelihood that the input image comes from a particular pose manifold and the transition probability to this pose manifold from the previous frame.
Proceedings ArticleDOI
Video-based face recognition using adaptive hidden Markov models
Xiaoming Liu,Tsuhan Cheng +1 more
TL;DR: This paper proposes to use adaptive hidden Markov models (HMM) to perform video-based face recognition and shows that the proposed algorithm results in better performance than using majority voting of image-based recognition results.
Proceedings ArticleDOI
A system identification approach for video-based face recognition
TL;DR: The paper poses video-to-video face recognition as a dynamical system identification and classification problem and uses an autoregressive and moving average (ARMA) model to represent such a system.
Journal ArticleDOI
Study of Implementing Automated Attendance System Using Face Recognition Technique
TL;DR: A method is described for Student's Attendance System which will integrate with the face recognition technology using Personal Component Analysis (PCA) algorithm and it will record the attendance of the students in class room environment automatically.
Journal ArticleDOI
Face recognition from video: a review
TL;DR: A broad and deep review of recently proposed methods for overcoming the difficulties encountered in unconstrained settings is presented and connections between the ways in which humans and current algorithms recognize faces are drawn.