计算机科学
Python(编程语言)
类似哈尔的特征
面部识别系统
人工智能
人脸检测
面子(社会学概念)
特征提取
计算机视觉
特征(语言学)
对象类检测
三维人脸识别
模式识别(心理学)
算法
语言学
哲学
社会科学
社会学
操作系统
作者
Xiaofei Song,Ming‐Ju Chen
标识
DOI:10.62517/jbdc.202401108
摘要
In order to understand the attendance of students in the classroom quickly and accurately, this paper proposes a classroom face recognition check-in algorithm developed based on Python language and OpenCV library. The Video Capture function provided by OpenCV library is used to call the camera for image acquisition, and then the acquired image is preprocessed to realize face detection using Haar-like features, the LBPH algorithm is used to extract features from the face image, and a training model is obtained through feature training and stored in the database. After the check-in is initiated, the acquired images are preprocessed, face detection and feature extraction are performed, and they are compared with the model previously stored in the database. The experimental results show that the algorithm is able to efficiently and accurately realize classroom face recognition check-in while ensuring lower cost.
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