Programming Computer Vision with Python

Jan Erik Solem (Autor)

Buch | Softcover

272 Seiten

2012
O'Reilly Media, Inc, USA (Verlag)
978-1-4493-1654-9 (ISBN)

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If you want a basic understanding of computer vision's underlying theory and algorithms, this hands-on introduction is the ideal place to start. As a student, researcher, hacker, or enthusiast, you'll learn as you follow examples written in Python - the easy-to-learn language that has modules for handling images and mathematical computing and data mining on a par with commercial alternatives. Programming Computer Vision with Python teaches computer vision in broad terms that won't bog you down in theory. Instead, you'll find this book to be inspiring and motivating. You'll get all the code you need, with clear explanations on how to reproduce the book's examples and build upon them directly.

If you want a basic understanding of computer vision’s underlying theory and algorithms, this hands-on introduction is the ideal place to start. You’ll learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, and other computer vision applications as you follow clear examples written in Python.
Programming Computer Vision with Python explains computer vision in broad terms that won’t bog you down in theory. You get complete code samples with explanations on how to reproduce and build upon each example, along with exercises to help you apply what you’ve learned. This book is ideal for students, researchers, and enthusiasts with basic programming and standard mathematical skills.

Learn techniques used in robot navigation, medical image analysis, and other computer vision applications
Work with image mappings and transforms, such as texture warping and panorama creation
Compute 3D reconstructions from several images of the same scene
Organize images based on similarity or content, using clustering methods
Build efficient image retrieval techniques to search for images based on visual content
Use algorithms to classify image content and recognize objects
Access the popular OpenCV library through a Python interface

Jan Erik Solem is a Python enthusiast and a computer vision researcher and entrepreneur. He is an applied mathematician and has worked as associate professor, startup CTO, and now also book author. He sometimes writes about computer vision and Python on his blog www.janeriksolem.net. He has used Python for computer vision in teaching, research and industrial applications for many years. He currently lives in San Francisco.

Chapter 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

Chapter 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

Chapter 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

Chapter 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

Chapter 6 Clustering Images

6.1 K-Means Clustering

6.2 Hierarchical Clustering

6.3 Spectral Clustering

Exercises

Chapter 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

Chapter 8 Classifying Image Content

8.1 K-Nearest Neighbors
8.2 Bayes Classifier
8.3 Support Vector Machines
8.4 Optical Character Recognition
Exercises

Chapter 9 Image Segmentation

9.1 Graph Cuts
9.2 Segmentation Using Clustering
9.3 Variational Methods
Exercises

Chapter 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 Installing Packages

A.1 NumPy and SciPy
A.2 Matplotlib
A.3 PIL
A.4 LibSVM
A.5 OpenCV
A.6 VLFeat
A.7 PyGame
A.8 PyOpenGL
A.9 Pydot
A.10 Python-graph
A.11 Simplejson
A.12 PySQLite
A.13 CherryPy

Appendix Image Datasets

B.1 Flickr
B.2 Panoramio
B.3 Oxford Visual Geometry Group
B.4 University of Kentucky Recognition Benchmark Images
B.5 Other

Appendix Image Credits

C.1 Images from Flickr
C.2 Other Images
C.3 Illustrations

Appendix References
Appendix About the Author
Colophon

"...eine hervorragende Lektüre für Praktiker, die nach den Prinzipien des Rapid Application Development (RAD) schnell Ergebnisse bei geringem Entwicklungsaufwand erzielen möchten." - Linux Magazin, 12/2012

Erscheint lt. Verlag	24.7.2012
Zusatzinfo	illustrations
Verlagsort	Sebastopol
Sprache	englisch
Maße	191 x 235 mm
Gewicht	431 g
Themenwelt	Informatik ► Programmiersprachen / -werkzeuge ► Python
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Mathematik / Informatik ► Informatik ► Web / Internet
ISBN-10	1-4493-1654-9 / 1449316549
ISBN-13	978-1-4493-1654-9 / 9781449316549
Zustand	Neuware