Learning OpenCV 3 computer Vision in C++ with the OpenCV Library
Get started in the rapidly expanding field of computer vision with this practical guide. Written by Adrian Kaehler and Gary Bradski, creator of the open source OpenCV library, this book provides a thorough introduction for developers, academics, roboticists, and hobbyists. You'll learn what it...
| Otros Autores: | , |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Beijing, [China] :
O'Reilly Media
2017.
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| Edición: | First edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630315006719 |
Tabla de Contenidos:
- 1. Overview
- 2. Introduction to OpenCV
- 3. Getting to know OpenCV data types
- 4. Images and Large Array Types
- 5. Array Operations
- 6. Drawing and Annotating
- 7. Functors in OpenCV
- 8. Image, Video, and Data Files
- 9. Cross-Platform and Native Windows
- 10. Filters and Convolution
- 11. General Image Transforms
- 12. Image Analysis
- 13. Histograms and Templates
- 14. Contours
- 15. Background Subtraction
- 16. Keypoints and Descriptors
- 17. Tracking
- 18. Camera Models and Calibration
- 19. Projection and Three-Dimensional Vision
- 20. The Basics of Machine Learning in OpenCV
- 21. StatModel: The Standard Model for Learning in OpenCV
- 22. Object Detection
- 23. Future of OpenCV
- A. Planar Subdivisions
- B. opencv_contrib
- C. Calibration Patterns.
