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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
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 [...] He has used Python for computer vision in teaching, research and industrial applications for many years. He currently lives in San Francisco.
Prerequisites and Overview;
Introduction to Computer Vision;
Python and NumPy;
Notation and Conventions;
Using Code Examples;
How to Contact Us;
Safari® Books Online;
Acknowledgments;
Chapter 1: Basic Image Handling and Processing;
1.1 1.1 PIL-The Python Imaging Library;
1.2 1.2 Matplotlib;
1.3 1.3 NumPy;
1.4 1.4 SciPy;
1.5 1.5 Advanced Example: Image De-Noising;
1.6 Exercises;
1.7 Conventions for the Code Examples;
Chapter 2: Local Image Descriptors;
2.1 2.1 Harris Corner Detector;
2.2 2.2 SIFT-Scale-Invariant Feature Transform;
2.3 2.3 Matching Geotagged Images;
2.4 Exercises;
Chapter 3: Image to Image Mappings;
3.1 3.1 Homographies;
3.2 3.2 Warping Images;
3.3 3.3 Creating Panoramas;
3.4 Exercises;
Chapter 4: Camera Models and Augmented Reality;
4.1 4.1 The Pin-Hole Camera Model;
4.2 4.2 Camera Calibration;
4.3 4.3 Pose Estimation from Planes and Markers;
4.4 4.4 Augmented Reality;
4.5 Exercises;
Chapter 5: Multiple View Geometry;
5.1 5.1 Epipolar Geometry;
5.2 5.2 Computing with Cameras and 3D Structure;
5.3 5.3 Multiple View Reconstruction;
5.4 5.4 Stereo Images;
5.5 Exercises;
Chapter 6: Clustering Images;
6.1 6.1 K-Means Clustering;
6.2 6.2 Hierarchical Clustering;
6.3 6.3 Spectral Clustering;
6.4 Exercises;
Chapter 7: Searching Images;
7.1 7.1 Content-Based Image Retrieval;
7.2 7.2 Visual Words;
7.3 7.3 Indexing Images;
7.4 7.4 Searching the Database for Images;
7.5 7.5 Ranking Results Using Geometry;
7.6 7.6 Building Demos and Web Applications;
7.7 Exercises;
Chapter 8: Classifying Image Content;
8.1 8.1 K-Nearest Neighbors;
8.2 8.2 Bayes Classifier;
8.3 8.3 Support Vector Machines;
8.4 8.4 Optical Character Recognition;
8.5 Exercises;
Chapter 9: Image Segmentation;
9.1 9.1 Graph Cuts;
9.2 9.2 Segmentation Using Clustering;
9.3 9.3 Variational Methods;
9.4 Exercises;
Chapter 10: OpenCV;
10.1 10.1 The OpenCV Python Interface;
10.2 10.2 OpenCV Basics;
10.3 10.3 Processing Video;
10.4 10.4 Tracking;
10.5 10.5 More Examples;
10.6 Exercises;
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;
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;
Image Credits;
C.1 Images from Flickr;
C.2 Other Images;
C.3 Illustrations;
References;
About the Author;
Colophon;
Erscheinungsjahr: | 2012 |
---|---|
Fachbereich: | Programmiersprachen |
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Inhalt: | 247 S. |
ISBN-13: | 9781449316549 |
ISBN-10: | 1449316549 |
Sprache: | Englisch |
Einband: | Kartoniert / Broschiert |
Autor: | Solem, Jan Erik |
Hersteller: |
O'Reilly Media
O'Reilly Media, Inc. |
Maße: | 231 x 179 x 17 mm |
Von/Mit: | Jan Erik Solem |
Erscheinungsdatum: | 24.07.2012 |
Gewicht: | 0,438 kg |
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 [...] He has used Python for computer vision in teaching, research and industrial applications for many years. He currently lives in San Francisco.
Prerequisites and Overview;
Introduction to Computer Vision;
Python and NumPy;
Notation and Conventions;
Using Code Examples;
How to Contact Us;
Safari® Books Online;
Acknowledgments;
Chapter 1: Basic Image Handling and Processing;
1.1 1.1 PIL-The Python Imaging Library;
1.2 1.2 Matplotlib;
1.3 1.3 NumPy;
1.4 1.4 SciPy;
1.5 1.5 Advanced Example: Image De-Noising;
1.6 Exercises;
1.7 Conventions for the Code Examples;
Chapter 2: Local Image Descriptors;
2.1 2.1 Harris Corner Detector;
2.2 2.2 SIFT-Scale-Invariant Feature Transform;
2.3 2.3 Matching Geotagged Images;
2.4 Exercises;
Chapter 3: Image to Image Mappings;
3.1 3.1 Homographies;
3.2 3.2 Warping Images;
3.3 3.3 Creating Panoramas;
3.4 Exercises;
Chapter 4: Camera Models and Augmented Reality;
4.1 4.1 The Pin-Hole Camera Model;
4.2 4.2 Camera Calibration;
4.3 4.3 Pose Estimation from Planes and Markers;
4.4 4.4 Augmented Reality;
4.5 Exercises;
Chapter 5: Multiple View Geometry;
5.1 5.1 Epipolar Geometry;
5.2 5.2 Computing with Cameras and 3D Structure;
5.3 5.3 Multiple View Reconstruction;
5.4 5.4 Stereo Images;
5.5 Exercises;
Chapter 6: Clustering Images;
6.1 6.1 K-Means Clustering;
6.2 6.2 Hierarchical Clustering;
6.3 6.3 Spectral Clustering;
6.4 Exercises;
Chapter 7: Searching Images;
7.1 7.1 Content-Based Image Retrieval;
7.2 7.2 Visual Words;
7.3 7.3 Indexing Images;
7.4 7.4 Searching the Database for Images;
7.5 7.5 Ranking Results Using Geometry;
7.6 7.6 Building Demos and Web Applications;
7.7 Exercises;
Chapter 8: Classifying Image Content;
8.1 8.1 K-Nearest Neighbors;
8.2 8.2 Bayes Classifier;
8.3 8.3 Support Vector Machines;
8.4 8.4 Optical Character Recognition;
8.5 Exercises;
Chapter 9: Image Segmentation;
9.1 9.1 Graph Cuts;
9.2 9.2 Segmentation Using Clustering;
9.3 9.3 Variational Methods;
9.4 Exercises;
Chapter 10: OpenCV;
10.1 10.1 The OpenCV Python Interface;
10.2 10.2 OpenCV Basics;
10.3 10.3 Processing Video;
10.4 10.4 Tracking;
10.5 10.5 More Examples;
10.6 Exercises;
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;
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;
Image Credits;
C.1 Images from Flickr;
C.2 Other Images;
C.3 Illustrations;
References;
About the Author;
Colophon;
Erscheinungsjahr: | 2012 |
---|---|
Fachbereich: | Programmiersprachen |
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Medium: | Taschenbuch |
Inhalt: | 247 S. |
ISBN-13: | 9781449316549 |
ISBN-10: | 1449316549 |
Sprache: | Englisch |
Einband: | Kartoniert / Broschiert |
Autor: | Solem, Jan Erik |
Hersteller: |
O'Reilly Media
O'Reilly Media, Inc. |
Maße: | 231 x 179 x 17 mm |
Von/Mit: | Jan Erik Solem |
Erscheinungsdatum: | 24.07.2012 |
Gewicht: | 0,438 kg |