Books & Videos

Table of Contents

  1. Chapter 1 Overview

    1. What Is OpenCV?

    2. Who Uses OpenCV?

    3. What Is Computer Vision?

    4. The Origin of OpenCV

    5. Downloading and Installing OpenCV

    6. Getting the Latest OpenCV via Git

    7. More OpenCV Documentation

    8. OpenCV Contribution Repository

    9. Portability

    10. Summary

    11. Exercises

  2. Chapter 2 Introduction to OpenCV

    1. Include Files

    2. First Program—Display a Picture

    3. Second Program—Video

    4. Moving Around

    5. A Simple Transformation

    6. A Not-So-Simple Transformation

    7. Input from a Camera

    8. Writing to an AVI File

    9. Summary

    10. Exercises

  3. Chapter 3 Getting to Know OpenCV Data Types

    1. The Basics

    2. OpenCV Data Types

    3. Summary

    4. Exercises

  4. Chapter 4 Images and Large Array Types

    1. Dynamic and Variable Storage

    2. Summary

    3. Exercises

  5. Chapter 5 Array Operations

    1. More Things You Can Do with Arrays

    2. Summary

    3. Exercises

  6. Chapter 6 Drawing and Annotating

    1. Drawing Things

    2. Summary

    3. Exercises

  7. Chapter 7 Functors in OpenCV

    1. Objects That “Do Stuff”

    2. Summary

    3. Exercises

  8. Chapter 8 Image, Video, and Data Files

    1. HighGUI: Portable Graphics Toolkit

    2. Working with Image Files

    3. Working with Video

    4. Data Persistence

    5. Summary

    6. Exercises

  9. Chapter 9 Cross-Platform and Native Windows

    1. Working with Windows

    2. Summary

    3. Exercises

  10. Chapter 10 Filters and Convolution

    1. Overview

    2. Before We Begin

    3. Threshold Operations

    4. Smoothing

    5. Derivatives and Gradients

    6. Image Morphology

    7. Convolution with an Arbitrary Linear Filter

    8. Summary

    9. Exercises

  11. Chapter 11 General Image Transforms

    1. Overview

    2. Stretch, Shrink, Warp, and Rotate

    3. General Remappings

    4. Image Repair

    5. Histogram Equalization

    6. Summary

    7. Exercises

  12. Chapter 12 Image Analysis

    1. Overview

    2. Discrete Fourier Transform

    3. Integral Images

    4. The Canny Edge Detector

    5. Hough Transforms

    6. Distance Transformation

    7. Segmentation

    8. Summary

    9. Exercises

  13. Chapter 13 Histograms and Templates

    1. Histogram Representation in OpenCV

    2. Basic Manipulations with Histograms

    3. Some More Sophisticated Histograms Methods

    4. Template Matching

    5. Summary

    6. Exercises

  14. Chapter 14 Contours

    1. Contour Finding

    2. More to Do with Contours

    3. Matching Contours and Images

    4. Summary

    5. Exercises

  15. Chapter 15 Background Subtraction

    1. Overview of Background Subtraction

    2. Weaknesses of Background Subtraction

    3. Scene Modeling

    4. Averaging Background Method

    5. A More Advanced Background Subtraction Method

    6. Connected Components for Foreground Cleanup

    7. Comparing Two Background Methods

    8. OpenCV Background Subtraction Encapsulation

    9. Summary

    10. Exercises

  16. Chapter 16 Keypoints and Descriptors

    1. Keypoints and the Basics of Tracking

    2. Generalized Keypoints and Descriptors

    3. Summary

    4. Exercises

  17. Chapter 17 Tracking

    1. Concepts in Tracking

    2. Dense Optical Flow

    3. Mean-Shift and Camshift Tracking

    4. Motion Templates

    5. Estimators

    6. Summary

    7. Exercises

  18. Chapter 18 Camera Models and Calibration

    1. Camera Model

    2. Calibration

    3. Undistortion

    4. Putting Calibration All Together

    5. Summary

    6. Exercises

  19. Chapter 19 Projection and Three-Dimensional Vision

    1. Projections

    2. Affine and Perspective Transformations

    3. Three-Dimensional Pose Estimation

    4. Stereo Imaging

    5. Structure from Motion

    6. Fitting Lines in Two and Three Dimensions

    7. Summary

    8. Exercises

  20. Chapter 20 The Basics of Machine Learning in OpenCV

    1. What Is Machine Learning?

    2. Legacy Routines in the ML Library

    3. Summary

    4. Exercises

  21. Chapter 21 StatModel: The Standard Model for Learning in OpenCV

    1. Common Routines in the ML Library

    2. Machine Learning Algorithms Using cv::StatModel

    3. Summary

    4. Exercises

  22. Chapter 22 Object Detection

    1. Tree-Based Object Detection Techniques

    2. Object Detection Using Support Vector Machines

    3. Summary

    4. Exercises

  23. Chapter 23 Future of OpenCV

    1. Past and Present

    2. How Well Did Our Predictions Go Last Time?

    3. Future Functions

    4. Some AI Speculation

    5. Afterword

  24. Appendix Planar Subdivisions

    1. Delaunay Triangulation, Voronoi Tesselation

    2. Exercises

  25. Appendix opencv_contrib

    1. An Overview of the opencv_contrib Modules

  26. Appendix Calibration Patterns

    1. Calibration Patterns Used by OpenCV