Human Face Detection and Recognition from the Video Using Deep Learning

Hemlata Sinha, Sumit Roy
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Abstract

            Attendance management can be a significant burden on teachers if done manually. To solve this problem, It is proposed that we use an intelligent and automatic presence management system. Using this framework, the problem of proxies and tagged students present while they are not physically present can easily be resolved. This system marks the attendance using live video stream. The frames are extracted from video using Open CV. The main implementation stages used in this type of system are detection and recognition of the detected face, for which dlib is used. After this, the connection of the acknowledged faces should be conceivable by comparing with the database containing the faces of the students. It will be an effective technique to manage student attendance..
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基于深度学习的视频人脸检测与识别
如果手工完成考勤管理,对教师来说可能是一个很大的负担。为了解决这一问题,我们提出了一种智能化、自动化的现场管理系统。使用这个框架,可以很容易地解决代理和标记学生在物理上不在场时在场的问题。该系统使用实时视频流标记考勤。使用Open CV从视频中提取帧。这类系统的主要实现阶段是检测和识别被检测的人脸,其中使用了dlib。在此之后,通过与包含学生面孔的数据库进行比较,可以想象识别的面孔之间的联系。管理学生出勤将是一种有效的方法。
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