Download free course Programming Computer Vision with Python, pdf file on 300 pages by Jan Erik Solem.
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
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
Table of contents
- Basic Image Handling and Processing
- Local Image Descriptors
- Image to Image Mappings
- Camera Models and Augmented Reality
- Multiple View Geometry
- Clustering Images
- Searching Images
- Classifying Image Content
- Image Segmentation
- OpenCV
- Installing Packages
- Image Datasets
- Image Credits
Pages : | 300 |
Size : | 13.6 MB |
Downloads: | 62 |
Created: | 2022-02-03 |
License: | CC BY-NC-ND |
Author(s): | Jan Erik Solem |
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