Mastering OpenCV with Practical Computer Vision Projects
I feel excited writing this post. The “Mastering OpenCV with Practical Computer Vision Projects” books is done and published! This is my first experience as a book author and i hope you will like it. This book has been written by several authors, and covers many topics that has real appliance in computer vision area: augmented reality, face recognition and head pose estimation, structure from motion estimation and cartoon image processing. We as authors made our best to bring the most popular and demanded topics to you.
Useful links
- Buy Mastering OpenCV with Practical Computer Vision Projects on Packt Publishing
- Buy “Mastering OpenCV with Practical Computer Vision Projects” from Amazon
- Buy “Mastering OpenCV with Practical Computer Vision Projects” (for Kindle) from Amazon
- Official code repository on GitHub
Table of contents
- Cartoonifier and Skin Changer for Android
- Marker-based Augmented Reality on iPhone or iPad
- Marker-less Augmented Reality
- Exploring Structure from Motion Using OpenCV
- Number Plate Recognition Using SVM and Neural Networks
- Non-rigid Face Tracking
- 3D Head Pose Estimation Using AAM and POSIT
- Face Recognition using Eigenfaces or Fisherfaces
Read before you buy it
You can read the entire chapter before buying the whole book! The “Exploring Structure from Motion Using OpenCV” chapter is available freely on Packt website: Read** Exploring Structure from Motion Using OpenCV** [PDF] chapter for free .
What you will learn from this book
- Perform Face Analysis including simple Face & Eye & Skin Detection, Fisherfaces Face Recognition, 3D Head Orientation, complex Facial Feature Tracking.
- Do Number Plate Detection and Optical Character Recognition (OCR) using Artificial Intelligence (AI) methods including SVMs and Neural Networks
- Learn Augmented Reality for desktop and iPhone or iPad using simple artificial markers or complex markerless natural images
- Generate a 3D object model by moving a plain 2D camera, using 3D Structure from Motion (SfM) camera reprojection methods
- Redesign desktop real-time computer vision applications to more suitable Android & iOS mobile apps
- Use simple image filter effects including cartoon, sketch, paint, and alien effects
- Execute Human-Computer Interaction with an XBox Kinect sensor using the whole body as a dynamic input