Programming Computer Vision with Python

Preface

1. Basic Image Handling and Processing
1.1 PIL—The Python Imaging Library
1.2 Matplotlib
1.3 NumPy
1.4 SciPy
1.5 Advanced Example: Image De-Noising
Exercises
Conventions for the Code Examples

2. Local Image Descriptors
2.1 Harris Corner Detector
2.2 SIFT—Scale-Invariant Feature Transform
2.3 Matching Geotagged Images
Exercises
Chapter 3 Image to Image Mappings
3.1 Homographies
3.2 Warping Images
3.3 Creating Panoramas
Exercises

4. Camera Models and Augmented Reality
4.1 The Pin-Hole Camera Model
4.2 Camera Calibration
4.3 Pose Estimation from Planes and Markers
4.4 Augmented Reality
Exercises

5. Multiple View Geometry
5.1 Epipolar Geometry
5.2 Computing with Cameras and 3D Structure
5.3 Multiple View Reconstruction
5.4 Stereo Images
Exercises

6. Clustering Images
6.1 K-Means Clustering
6.2 Hierarchical Clustering
6.3 Spectral Clustering
Exercises

7. Searching Images
7.1 Content-Based Image Retrieval
7.2 Visual Words
7.3 Indexing Images
7.4 Searching the Database for Images
7.5 Ranking Results Using Geometry
7.6 Building Demos and Web Applications
Exercises

8. Classifying Image Content
8.1 K-Nearest Neighbors
8.2 Bayes Classifier
8.3 Support Vector Machines
8.4 Optical Character Recognition

9. Image Segmentation
9.1 Graph Cuts
9.2 Segmentation Using Clustering
9.3 Variational Methods
Exercises

10. OpenCV
10.1 The OpenCV Python Interface
10.2 OpenCV Basics
10.3 Processing Video
10.4 Tracking
10.5 More Examples
Exercises

Appendix A: Installing Packages
Appendix B: Image Datasets
Appendix C: Image Credits

References
Index