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Real-Time Group Face-Detection for an Intelligent Class-Attendance System

机译:智能班级考勤系统的实时小组人脸检测

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The traditional manual attendance system wastes time over students’ responses, but it has worked well for small numbers of students. This research presents a real-time group face-detection system. This system will be used later for student class attendance through automatic student identification. The system architecture and its algorithm will be described in details. The algorithm for the system was based on analyzing facial properties and features in order to perform face detection for checking students’ attendance in real time. The classroom’s camera captures the students’ photo. Then, face detection will be implemented automatically to generate a list of detected student faces. Many experiments were adopted based on real time video captured using digital cameras. The experimental results showed that our approach of face detection offers real-time processing speed with good acceptable detection ratio equal to 94.73%.
机译:传统的手动出勤系统浪费时间浪费在学生的回答上,但对少数学生来说效果很好。这项研究提出了一种实时的人脸检测系统。该系统将在以后通过自动识别学生身份用于学生课堂出勤。将详细描述系统架构及其算法。该系统的算法基于分析面部特征和特征,以便执行面部检测以实时检查学生的出勤情况。教室的相机拍摄学生的照片。然后,将自动执行面部检测以生成检测到的学生面部列表。基于使用数码相机捕获的实时视频,进行了许多实验。实验结果表明,我们的人脸检测方法提供了实时的处理速度,良好的可接受检测率达到94.73%。

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