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深度解析OpenCV实践项目：高清英文版

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"《深入理解OpenCV：实用计算机视觉项目解析》是一本专为计算机视觉技术爱好者和专业人士精心编撰的高清英文版教程。本书由Daniel Lélis Baggio、Shervin Emami、David Millán Escrivá等多位作者共同编写，涵盖了广泛的实际项目案例，旨在帮助读者逐步解决从增强现实、车牌识别到人脸识别、3D头跟踪等各种常见且实用的计算机视觉问题。读者无论是在桌面开发还是移动应用领域，都能在本书中找到针对性的解决方案。这本书以实践为导向，通过一系列step-by-step的教学方法，引导读者深入理解OpenCV库的工作原理，以及如何将其应用于实际场景。OpenCV（Open Source Computer Vision Library）是一个开源的计算机视觉和机器学习库，它为开发人员提供了丰富的图像处理和计算机视觉算法，对于提高图像分析、物体检测和识别能力具有重要作用。版权方面，该书受2012年Packt Publishing出版，所有内容未经事先书面许可不得复制、存储或任何形式传播，除非在学术文章或评论中进行简短引用。尽管作者和出版社尽力确保信息的准确性，但书中提供的信息不带有任何形式的保修，作者、Packt Publishing及其经销商和分销商不对由此书引起的直接或间接损害承担法律责任。《深入理解OpenCV：实用计算机视觉项目解析》是一本极具价值的学习资源，适合希望提升计算机视觉技能的开发者，无论是为了个人兴趣还是职业发展，都能从中获益匪浅。通过跟随书中的实例，读者可以扎实掌握OpenCV的核心功能，并将其运用到自己的项目中，从而推动技术创新和应用创新。"

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Table of Contents

[ iii ]

Creating OpenGL windows using OpenCV 118

Video capture using OpenCV 118

Rendering augmented reality 119

ARDrawingContext.hpp 119

ARDrawingContext.cpp 120

Demonstration 122

main.cpp 123

Summary 126

References 127

Chapter 4: Exploring Structure from Motion Using OpenCV 129

Structure from Motion concepts 130

Estimating the camera motion from a pair of images 132

Point matching using rich feature descriptors 132

Point matching using optical ow 134

Finding camera matrices 139

Reconstructing the scene 143

Reconstruction from many views 147

Renement of the reconstruction 151

Visualizing 3D point clouds with PCL 155

Using the example code 158

Summary 159

References 160

Chapter 5: Number Plate Recognition Using SVM and

Neural Networks 161

Introduction to ANPR 161

ANPR algorithm 163

Plate detection 166

Segmentation 167

Classication 173

Plate recognition 176

OCR segmentation 177

Feature extraction 178

OCR classication 181

Evaluation 185

Summary 188

Chapter 6: Non-rigid Face Tracking 189

Overview 191

Utilities 191

Object-oriented design 191

Table of Contents

[ iv ]

Data collection: Image and video annotation 193

Training data types 194

Annotation tool 198

Pre-annotated data (The MUCT dataset) 198

Geometrical constraints 199

Procrustes analysis 202

Linear shape models 205

A combined local-global representation 207

Training and visualization 209

Facial feature detectors 212

Correlation-based patch models 214

Learning discriminative patch models 214

Generative versus discriminative patch models 218

Accounting for global geometric transformations 219

Training and visualization 222

Face detection and initialization 224

Face tracking 228

Face tracker implementation 229

Training and visualization 231

Generic versus person-specic models 232

Summary 233

References 233

Chapter 7: 3D Head Pose Estimation Using AAM and POSIT 235

Active Appearance Models overview 236

Active Shape Models 238

Getting the feel of PCA 240

Triangulation 245

Triangle texture warping 247

Model Instantiation – playing with the Active Appearance Model 249

AAM search and tting 250

POSIT 253

Diving into POSIT 253

POSIT and head model 256

Tracking from webcam or video le 257

Summary 259

References 260

Chapter 8: Face Recognition using Eigenfaces or Fisherfaces 261

Introduction to face recognition and face detection 261

Step 1: Face detection 263

Implementing face detection using OpenCV 264

Loading a Haar or LBP detector for object or face detection 265

Accessing the webcam 266

Table of Contents

[ v ]

Detecting an object using the Haar or LBP Classier 266

Detecting the face 268

Step 2: Face preprocessing 270

Eye detection 271

Eye search regions 272

Step 3: Collecting faces and learning from them 281

Collecting preprocessed faces for training 283

Training the face recognition system from collected faces 285

Viewing the learned knowledge 287

Average face 289

Eigenvalues, Eigenfaces, and Fisherfaces 290

Step 4: Face recognition 292

Face identication: Recognizing people from their face 292

Face verication: Validating that it is the claimed person 292

Finishing touches: Saving and loading les 295

Finishing touches: Making a nice and interactive GUI 295

Drawing the GUI elements 297

Checking and handling mouse clicks 306

Summary 308

References 309

Index 311

Preface

Mastering OpenCV with Practical Computer Vision Projects contains nine chapters, where

each chapter is a tutorial for an entire project from start to nish, based on OpenCV's

C++ interface including full source code. The author of each chapter was chosen for

their well-regarded online contributions to the OpenCV community on that topic,

and the book was reviewed by one of the main OpenCV developers. Rather than

explaining the basics of OpenCV functions, this is the rst book that shows how

to apply OpenCV to solve whole problems, including several 3D camera projects

(augmented reality, 3D Structure from Motion, Kinect interaction) and several facial

analysis projects (such as, skin detection, simple face and eye detection, complex facial

feature tracking, 3D head orientation estimation, and face recognition), therefore it

makes a great companion to existing OpenCV books.

What this book covers

Chapter 1, Cartoonier and Skin Changer for Android, contains a complete tutorial and

source code for both a desktop application and an Android app that automatically

generates a cartoon or painting from a real camera image, with several possible types

of cartoons including a skin color changer.

Chapter 2, Marker-based Augmented Reality on iPhone or iPad, contains a complete

tutorial on how to build a marker-based augmented reality (AR) application for

iPad and iPhone devices with an explanation of each step and source code.

Chapter 3, Marker-less Augmented Reality, contains a complete tutorial on how to

develop a marker-less augmented reality desktop application with an explanation

of what marker-less AR is and source code.

Chapter 4, Exploring Structure from Motion Using OpenCV, contains an introduction

to Structure from Motion (SfM) via an implementation of SfM concepts in OpenCV.

The reader will learn how to reconstruct 3D geometry from multiple 2D images and

estimate camera positions.

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深度解析OpenCV实践项目：高清英文版

深入理解OpenCV 实用计算机视觉项目解析-源代码

学习opencv（中文版+英文版PDF电子书+原书代码很全的）

深入理解OpenCV实用计算机视觉项目解析预览版

深入理解OpenCV中的计算机视觉算法与应用

深入理解OpenCV中图像读取和处理的原理

深入理解OpenCV图像几何变换：常见问题与解决方案

深入理解OpenCV中的立体视觉与三维重建技术

VSCode 中 OpenCV 的图像配准：深入理解与应用

头文件是opencv2/opencv.cpp这是哪个版本的opencv

OpenCvSharp.Blob.dll can't find

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opencv_world411.lib

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opencv_java460.dll下载

c++的opencv2/opencv.hpp下载

fatal error<opencv2\opencv.hpp>的原因

1 30 D:\Download\opencv.cpp [Error] opencv2/opencv.hpp: No such file or directory compilation terminated.

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<opencv2/opencv.hpp> 无法打开源文件"opencv2/opencv.hpp