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所在平台: Udemy |
课程主页: https://www.udemy.com/course/computer-vision-bootcamp-build-face-recognition-with-opencv/
课程评论：没有评论
课程名称：计算机视觉训练营：使用OpenCV构建面部识别系统 概述：欢迎参加“计算机视觉训练营：使用OpenCV构建面部识别系统”课程。本课程是一个以项目为基础的全面课程，您将逐步学习如何使用OpenCV构建面部识别系统、情感检测系统、年龄检测系统和眼动追踪系统。该课程结合了计算机视觉和图像处理的关键技能，帮助您掌握特征提取和模式识别的基本技能，使您能够开发复杂的面部识别系统。 在介绍环节，您将了解面部识别的基本原理、应用案例、使用的技术及其局限性。接下来，您将学习面部识别技术的工作原理，包括数据收集、预处理、模型训练、特征提取和人脸匹配。 课程主要项目分为几个部分： 1. **面部识别系统：** 创建用于身份验证的面部识别系统，准备训练数据（姓名、照片、年龄和性别），训练模型以验证面部结构分析，成功匹配后显示“访问已授权”，否则显示“访问被拒”。 2. **情感检测系统：** 使用Kaggle获取数据集，训练模型以检测情感和面部表情。 3. **年龄检测系统：** 利用包含不同年龄人的照片的数据集，训练模型预测个体的年龄。 4. **眼动追踪系统：** 分析学生在在线考试中的眼动模式，并在检测到可疑行为时通知教师，帮助维护在线课堂的学术诚信。 通过本课程，您将学习到以下内容： - 面部识别技术的基本原理、应用案例、使用的技术与局限性 - 面部识别系统的工作流程，包括数据收集、预处理、模型训练等 - 使用OpenCV激活相机 - 构建面部识别系统 - 创建面部识别系统的训练数据 - 加载图像、进行面部特征提取和访问管理 - 使用Keras训练情感检测模型 - 使用OpenCV构建情感检测、年龄检测和眼动追踪系统。 该课程旨在帮助学员掌握面部识别系统的构建与应用，为安全性和身份验证提供支持。
Welcome to Computer Vision Bootcamp: Building Face Recognition with OpenCV course. This is a comprehensive projects based course where you will learn step by step on how to build a face recognition system, emotion detection system, age detection system, and eye tracking system using OpenCV. This course is a perfect combination between computer vision and image processing. This course will equip you with essential skills in feature extraction and pattern recognition, enabling you to develop complex facial recognition systems. In the introduction session, you will learn about the basic fundamentals of facial recognition, such as getting to know its use cases, technologies that will be used, and its limitations. Then, in the next session, you will learn how facial recognition technology works. This section will cover data collection, preprocessing, model training, feature extraction, and face matching. Afterward, we will start the project section, in the first section, we will build facial recognition for the identity verification system. Firstly, we are going to prepare the training data. It consists of several information like name, photo, age, and gender. Then, the data will be used to train the facial recognition model and it will enable the model to verify if you are the same person as the stored data based on the facial structure analysis. In addition, the model will also be able to make a decision, if the face matched then the model will print, access granted, however if the face did not match, then, the model will print, access denied. Meanwhile, in the second project section, we will build an emotion detection system using OpenCV. In this case, we will obtain a dataset from Kaggle and use that data to train the model to be able to detect emotion and facial expression. Then, in the third project section, we will build an age detection system using OpenCV. We will use a dataset containing photos of people from various ages and use it to train the model to predict someone's age based on their facial structure. In the fourth project section, we will build an eye tracking system that can be utilized to analyze movements of a student's eyes to monitor their gaze patterns during an online exam. In addition, the model will also be able to notify the teacher if suspicious behavior is detected. This technology can potentially help teachers and college professors to maintain the academic integrity in their online class.First of all, before getting into the course, we need to ask ourselves this question: why should we build facial recognition systems? Well, here is my answer: facial recognition systems play a pivotal role in supporting security measures across various sectors, including banking, government, and corporate environments. By accurately identifying individuals based on unique facial features, these systems provide a robust means of access control, ensuring only authorized personnel can gain entry to restricted areas or sensitive information. Moreover, in the digital world, facial recognition serves as a powerful tool for identity verification and authentication, safeguarding online accounts, transactions, and personal data from unauthorized access or fraudulent activities. Its ability to verify identity in real time offers unparalleled security and convenience, mitigating risks associated with traditional authentication methods like passwords or PINs, which are susceptible to theft or exploitation. As the threat landscape continues to evolve, the adoption of facial recognition technology remains paramount in safeguarding assets, maintaining trust, and upholding the integrity of digital ecosystemsBelow are things that you can expect to learn from this course:Learn the basics fundamentals of facial recognition technology, such as getting to know its use cases, technologies used, and limitationsLearn how facial recognition systems work. This section will cover data collection, data preprocessing, model training, scanning face, image preprocessing, face features extraction, and access managementLearn how to activate camera using OpenCVLearn how to build facial recognition system using OpenCVLearn how to create training data for facial recognition systemLearn how to create function to load images from training data folderLearn how to create access management and identity verification systemLearn how to draw rectangle around faceLearn how to train emotion detection model using KerasLearn how to build emotion detection system using OpenCVLearn how to build age detection system using OpenCVLearn how to build eye tracking system using OpenCV
