Mastering OpenCV 4: A comprehensive guide to building computer vision and image processing applications with C++, 3/e (Paperback)
暫譯: 精通 OpenCV 4:使用 C++ 建立電腦視覺與影像處理應用的全面指南(第三版,平裝本)

Roy Shilkrot, David Millan Escriva

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商品描述

Work on practical computer vision projects covering advanced object detector techniques and modern deep learning and machine learning algorithms

Key Features

  • Learn about the new features that help unlock the full potential of OpenCV 4
  • Build face detection applications with a cascade classifier using face landmarks
  • Create an optical character recognition (OCR) model using deep learning and convolutional neural networks

Book Description

Mastering OpenCV, now in its third edition, targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, the book delivers complete projects from ideation to running code, targeting current hot topics in computer vision such as face recognition, landmark detection and pose estimation, and number recognition with deep convolutional networks.

You'll learn from experienced OpenCV experts how to implement computer vision products and projects both in academia and industry in a comfortable package. You'll get acquainted with API functionality and gain insights into design choices in a complete computer vision project. You'll also go beyond the basics of computer vision to implement solutions for complex image processing projects.

By the end of the book, you will have created various working prototypes with the help of projects in the book and be well versed with the new features of OpenCV4.

What you will learn

  • Build real-world computer vision problems with working OpenCV code samples
  • Uncover best practices in engineering and maintaining OpenCV projects
  • Explore algorithmic design approaches for complex computer vision tasks
  • Work with OpenCV's most updated API (v4.0.0) through projects
  • Understand 3D scene reconstruction and Structure from Motion (SfM)
  • Study camera calibration and overlay AR using the ArUco Module

Who this book is for

This book is for those who have a basic knowledge of OpenCV and are competent C++ programmers. You need to have an understanding of some of the more theoretical/mathematical concepts, as we move quite quickly throughout the book.

Table of Contents

  1. Cartoonifier and Skin Color Analysis on the RaspberryPi
  2. Exploring Structure from Motion with the SfM Module
  3. Face Landmark and Pose Estimation with the Face Module
  4. Number Plate Recognition with Deep Convolutional Networks
  5. Face Recognition with the DNN Module
  6. Introduction to Web Computer Vision with OpenCv.js
  7. Android Camera Calibration and AR using the ARUco Module
  8. iOS Image Stitching with the Stitching Module
  9. Finding the Best OpenCV Algorithm for the Job
  10. Avoiding Common Pitfalls in OpenCV

商品描述(中文翻譯)

**實作涵蓋先進物件偵測技術及現代深度學習和機器學習演算法的計算機視覺專案**

#### 主要特色

- 了解幫助釋放 OpenCV 4 完整潛力的新功能
- 使用面部地標和級聯分類器建立面部偵測應用程式
- 使用深度學習和卷積神經網絡創建光學字符識別 (OCR) 模型

#### 書籍描述

《精通 OpenCV》第三版針對計算機視覺工程師,幫助他們邁出精通 OpenCV 的第一步。書中將數學公式保持在堅實但簡約的最低限度,提供從構思到運行代碼的完整專案,針對計算機視覺中的熱門主題,如面部識別、地標偵測、姿勢估計以及使用深度卷積網絡的數字識別。

您將從經驗豐富的 OpenCV 專家那裡學習如何在學術界和工業界實施計算機視覺產品和專案,並以舒適的方式進行學習。您將熟悉 API 功能,並深入了解完整計算機視覺專案中的設計選擇。您還將超越計算機視覺的基礎,為複雜的影像處理專案實施解決方案。

在書籍結束時,您將能夠利用書中的專案創建各種可運行的原型,並熟悉 OpenCV 4 的新功能。

#### 您將學到的內容

- 使用可運行的 OpenCV 代碼範例構建現實世界的計算機視覺問題
- 揭示工程和維護 OpenCV 專案的最佳實踐
- 探索複雜計算機視覺任務的演算法設計方法
- 通過專案使用 OpenCV 最新的 API (v4.0.0)
- 理解 3D 場景重建和運動結構 (SfM)
- 研究相機校準和使用 ArUco 模組進行增強現實 (AR)

#### 本書適合誰

本書適合對 OpenCV 有基本了解且具備 C++ 編程能力的人士。您需要理解一些較為理論/數學的概念,因為我們在書中會相當快速地進行。

#### 目錄

1. 在 RaspberryPi 上的卡通化和膚色分析
2. 使用 SfM 模組探索運動結構
3. 使用面部模組進行面部地標和姿勢估計
4. 使用深度卷積網絡進行車牌識別
5. 使用 DNN 模組進行面部識別
6. 使用 OpenCv.js 進行網頁計算機視覺介紹
7. 使用 ARUco 模組進行 Android 相機校準和增強現實
8. 使用拼接模組進行 iOS 圖像拼接
9. 尋找最適合工作的 OpenCV 演算法
10. 避免 OpenCV 中的常見陷阱