The Use of Local Sensitive Hashing for E-learner Face Identification

Hachem H. Alaoui, El-Kaber Hachem, C. Ziti, Mohammed Karim
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Abstract

Because face can reveal so much hidden information, we need to interpret these data and benefit from them. Hence, our paper shows a new and productive facial image representation based on local sensitive hashing (LSH). This strategy makes it conceivable to recognize the students who pursue their preparation in our learning training; during every session, an image of the learner will be taken by the webcam to be compared to that already stored in the database. As soon as the learner is recognized, he/she must be arranged in the accordion to an appropriate profile that takes into consideration his/her weaknesses and strength, which is conducted with the help of the J48 as a predictive study. Furthermore, we utilize a light processing module on the client device with a compact code in order that we can have a lot of in formation transmission capable to send the component over the network and to have the option to record many photos in an enormous database in the cloud.
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局部敏感哈希法在在线学习者人脸识别中的应用
因为人脸可以揭示很多隐藏的信息,我们需要解读这些数据并从中受益。因此,本文提出了一种新的基于局部敏感哈希(LSH)的高效面部图像表示方法。这一策略使得在我们的学习训练中识别那些追求准备的学生成为可能;在每次学习过程中,网络摄像头都会拍摄学习者的图像,并将其与数据库中已经存储的图像进行比较。一旦学习者被识别出来,就必须考虑到他/她的弱点和优势,将他/她按手风琴排列成适当的轮廓,这是在J48的帮助下进行的,作为一项预测性研究。此外,我们利用客户端设备上的光处理模块和紧凑的代码,以便我们可以有大量的信息传输,能够通过网络发送组件,并可以选择在云中的庞大数据库中记录许多照片。
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