基于人工智能的图书馆学生学习状态监测技术研究

Research on Student Learning State Monitoring Technology for Library Based on Artificial Intelligence

为提高高校图书馆学生学习状态监测的智能化水平,研究了基于人工智能的学生学习状态监测技术。研究通过基于级联回归的算法对学生人脸面部特征点提取,识别眨眼、打哈欠等状态,并通过对头部姿态信息的估计,分析学生的学习状态。通过摄像头采集图像信息,对算法进行实验测试,结果表明:研究的方法能够对学生眨眼、打哈欠和瞌睡点头等状态进行智能监测,根据监测结果通过提醒等方式可服务于学生学习效率提升。该系统为提高图书馆自习室、研修室共享资源的利用率提供了有效解决方法,对提高高校图书馆智能化管理水平有一定的应用意义。

To improve the intelligentization level of student learning status monitoring in university libraries,the monitoring technology of student learning status based on artificial intelligence is studied.An algorithm based on cascade regression is used to extract facial fea-ture points of students,recognizing blinking,yawning and other states,then students’learning state is analyzed through the estimation of head posture information.The image information is collected by the camera,and the algorithm is tested experimentally.The results dem-onstrate that the method can intelligently monitor the students’blinking,yawning,dozing and other states,and can serve the improve-ment of students’learning efficiency through reminders and other means according to the monitoring results.This system provides an ef-fective solution for improving the utilization rate of shared resources in the self-study room and research room of the library,and has cer-tain application significance for improving the intelligent management level of university libraries.