It is human nature to give prime importance to facial appearances. Often, to look good is to feel good. Also, facial features are unique to every individual on this planet, which means it is a source of vital information. This work proposes a framework named E-Pro for the detection and recognition of faces by taking facial images as inputs. E-Pro has its potential application in various domains, namely attendance, surveillance, crowd monitoring, biometric-based authentication etc. E-Pro is developed here as a mobile application that aims to aid lecturers to mark attendance in a classroom by detecting and recognizing the faces of students from a picture clicked through the app. E-Pro has been developed using Google Firebase Face Recognition APIs, which uses Euler Angles, and Probabilistic Model. E-Pro has been tested on stock images and the experimental results are promising.
翻译:将面部外观放在首要地位是人性性的。 通常, 看上去良好是感觉良好。 另外, 面部特征是地球上每个人独有的, 这意味着它是一个重要信息的来源。 这项工作提出了一个名为E-Pro的框架, 用于通过将面部图像作为投入来检测和识别面部。 E-Pro有可能在各个领域应用, 包括出勤、 监视、 人群监测、 基于生物鉴别的认证等。 E- Pro在这里开发成一个移动应用程序, 目的是帮助讲师通过检测和识别通过应用程序点击的图片显示学生的面部。 E- Pro是使用Google Firebase脸部识别APIs(Euler Agles)和概率模型开发的。 E- Pro已经对股票图像进行了测试,实验结果很有希望。