This is the definitive advanced tutorial for OpenCV, designed for those with basic C++ skills. The computer vision projects are divided into easily assimilated chapters with an emphasis on practical involvement for an easier learning curve.
Overview
- Allows anyone with basic OpenCV experience to rapidly obtain skills in many computer vision topics, for research or commercial use
- Each chapter is a separate project covering a computer vision problem, written by a professional with proven experience on that topic.
- All projects include a step-by-step tutorial and full source-code, using the C++ interface of OpenCV.
In Detail
Computer Vision is fast becoming an important technology and is used in Mars robots, national security systems, automated factories, driver-less cars, and medical image analysis to new forms of human-computer interaction. OpenCV is the most common library for computer vision, providing hundreds of complex and fast algorithms. But it has a steep learning curve and limited in-depth tutorials.
Mastering OpenCV with Practical Computer Vision Projects is the perfect book for developers with just basic OpenCV skills who want to try practical computer vision projects, as well as the seasoned OpenCV experts who want to add more Computer Vision topics to their skill set or gain more experience with OpenCV's new C++ interface before migrating from the C API to the C++ API.
Each chapter is a separate project including the necessary background knowledge, so try them all one-by-one or jump straight to the projects you're most interested in.
Create working prototypes from this book including real-time mobile apps, Augmented Reality, 3D shape from video, or track faces & eyes, fluid wall using Kinect, number plate recognition and so on.
Mastering OpenCV with Practical Computer Vision Projects gives you rapid training in nine computer vision areas with useful projects.
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
Approach
Each chapter in the book is an individual project and each project is constructed with step-by-step instructions, clearly explained code, and includes the necessary screenshots.
Who this book is written for
You should have basic OpenCV and C/C++ programming experience before reading this book, as it is aimed at Computer Science graduates, researchers, and computer vision experts widening their expertise.
Daniel Lélis Baggio
Daniel Lélis Baggio started his work in computer vision through medical image processing at InCor (Instituto do Coração Heart Institute) in São Paulo, where he worked with intra-vascular ultrasound image segmentation. Since then, he has focused on GPGPU and ported the segmentation algorithm to work with NVIDIA's CUDA. He has also dived into six degrees of freedom head tracking with a natural user interface group through a project called ehci (http://code.google.com/p/ehci/). He now works for the Brazilian Air Force.
