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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.
Table of Contents
1: CARTOONIFIER AND SKIN CHANGER FOR ANDROID
2: MARKER-BASED AUGMENTED REALITY ON IPHONE OR IPAD
3: MARKER-LESS AUGMENTED REALITY
4: EXPLORING STRUCTURE FROM MOTION USING OPENCV
5: NUMBER PLATE RECOGNITION USING SVM AND NEURAL NETWORKS
6: NON-RIGID FACE TRACKING
7: 3D HEAD POSE ESTIMATION USING AAM AND POSIT
8: FACE RECOGNITION USING EIGENFACES OR FISHERFACES
What You Will Learn
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