Hybrid Architecture of Face and Action Recognition Systems for Proctoring on a Graphic Processor

Aksultan Mukhanbet, E. S. Nurakhov, Timur Imankulov

2021

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DOI 10.1109/sist50301.2021.9465971
Data confidence 70 medium
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Abstract

A solution has been developed due to problem of face recognition and actions when we are trying to process images of human faces in real time on the server. Approaches to solving the problem of face recognition and actions on images are considered. The solution of the problem of action's recognition in real time is considered. An action recognition system was used for proctoring.A hybrid architecture was developed for face and action recognition. The FaceNet algorithm was used to implement the system. We used the faces of a person that was filmed to collect the dataset. The results obtained show a high accuracy of the face recognition percentage. Face and motion recognition is implemented in Windows Server 2016. A special web application was developed to test these algorithms.To reduce processing time and recognition algorithms were used like bandwidth, resize images. In addition, the entire process of video processing for proctoring was launched in the graphics server. With the web app, you can see how well the face recognition algorithm and the result of the action recognition algorithm are.