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所在平台: Udemy |
课程主页: https://www.udemy.com/course/the-ultimate-beginners-guide-facial-detection-recognition/
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课程名称: 《人脸检测与识别终极初学者指南》 课程概述: 人脸检测是计算机视觉的一个子领域，旨在在图像或视频中检测人脸。智能手机和数码相机使用此功能选择照片中的人物，通常会在脸部周围划出矩形框。这类应用在安全系统中尤为重要，系统需识别环境中是否有人以触发警报。另一方面，人脸识别则旨在识别个体的面部特征，例如安全系统利用这一功能判断某人在场与否。需要强调的是，人脸检测和识别技术之间的区别：前者仅指示是否存在脸部，而后者则指明检测到的是哪张脸。 在本课程中，您将逐步学习如何使用Python编程语言，从基础到高级技术，检测和识别人脸，包括图像、视频和网络摄像头。以下是将要涵盖的主题： - 使用Haarcascade、HOG（方向梯度直方图）、MMOD（最大边界物体检测）和SSD（单次多框检测器）进行人脸检测 - 检测其他对象，如眼睛、微笑、时钟、身体和汽车 - 使用Eigenfaces、Fisherfaces、LBPH（局部二值模式直方图）和高级深度学习技术进行人脸识别 - 性能比较算法 - 通过网络摄像头捕获面部构建自定义数据集 所有的实现都将通过Google Colab在线进行，您无需担心在自己机器上安装和配置工具！课程包括60多节讲座和8小时的逐步视频教程！
Facial detection is a subarea of Computer Vision that aims to detect people's faces in images or videos. Smartphones and digital cameras use these features to select people in a photo, usually placing a rectangle around the face. This type of application has gained considerable relevance in security systems, in which it is necessary to identify whether there are people in an environment for the alarm to be triggered. On the other hand, facial recognition aims to recognize people's faces and one example is security systems that can use these features to identify whether or not a person is present in an environment. It is important to highlight the differences between face detection and recognition techniques: while the first only indicates if a face is present, the second indicates whose face is detected.In this step by step course using Python programming language, you are going to learn how to detect and recognize faces from images, videos and webcam from the most basic to the most advanced techniques! See below the topics that you be covered:Detection of faces using Haarcascade, HOG (Histogram of Oriented Gradients), MMOD (Max-Margin Object Detection), and SSD (Single Shot Multibox Detector)Detection of other objects, such as eyes, smiles, clocks, bodies, and carsRecognition of faces using Eigenfaces, Fisherfaces, LBPH (Local Binary Patterns Histograms), and advanced Deep Learning techniquesHow to compare the performance of the algorithmsBuild your custom dataset capturing faces via webcamAll implementations will be done step by step using Google Colab online, so you do not need to worry about installing and configuring the tools on your own machine! More than 60 lectures and 8 hours of step by step videos!
