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Mastering OpenCV with Practical Computer Vision Projects.

By: Emami, ShervinContributor(s): Levgen, KhvedcheniaMaterial type: TextTextPublication details: Birmingham : Packt Pub., 2012. Description: 1 online resource (701 pages)Content type: text Media type: computer Carrier type: online resourceISBN: 9781849517836; 1849517835Subject(s): OpenCV | Computer vision | COMPUTERS -- General | Computer visionGenre/Form: Electronic books. | Electronic books. Additional physical formats: Print version:: Mastering OpenCV with Practical Computer Vision Projects.DDC classification: 006.3 | 006.37 LOC classification: TA1634Online resources: Click here to access online
Contents:
Table of Contents; Mastering OpenCV with Practical Computer Vision Projects; Mastering OpenCV with Practical Computer Vision Projects; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Support files, eBooks, discount offers and more; Why Subscribe?; Free Access for Packt account holders; Preface; What this book covers; What you need for this book; Who this book is for; Conventions; Reader feedback; Customer support; Downloading the example code; Errata; Piracy; Questions; 1. Cartoonifier and Skin Changer for Android; Accessing the webcam.
Main camera processing loop for a desktop appGenerating a black-and-white sketch; Generating a color painting and a cartoon; Generating an ""evil"" mode using edge filters; Generating an ""alien"" mode using skin detection; Skin-detection algorithm; Showing the user where to put their face; Implementation of the skin-color changer; Porting from desktop to Android; Setting up an Android project that uses OpenCV; Color formats used for image processing on Android; Input color format from the camera; Output color format for display; Adding the cartoonifier code to the Android NDK app.
Reviewing the Android appCartoonifying the image when the user taps the screen; Saving the image to a file and to the Android picture gallery; Showing an Android notification message about a saved image; Changing cartoon modes through the Android menu bar; Reducing the random pepper noise from the sketch image; Showing the FPS of the app; Using a different camera resolution; Customizing the app; Summary; 2. Marker-based Augmented Reality on iPhone or iPad; Creating an iOS project that uses OpenCV; Adding OpenCV framework; Including OpenCV headers; Application architecture.
Accessing the cameraMarker detection; Marker identification; Grayscale conversion; Image binarization; Contours detection; Candidates search; Marker code recognition; Reading marker code; Marker location refinement; Placing a marker in 3D; Camera calibration; Marker pose estimation; Rendering the 3D virtual object; Creating the OpenGL rendering layer; Rendering an AR scene; Summary; References; 3. Marker-less Augmented Reality; Marker-based versus marker-less AR; Using feature descriptors to find an arbitrary image on video; Feature extraction; Definition of a pattern object.
Matching of feature pointsPatternDetector.cpp; Outlier removal; Cross-match filter; Ratio test; PatternDetector.cpp; Homography estimation; PatternDetector.cpp; Homography refinement; PatternDetector.cpp; Putting it all together; Pattern pose estimation; PatternDetector.cpp; Obtaining the camera-intrinsic matrix; Pattern.cpp; Application infrastructure; ARPipeline.hpp; ARPipeline.cpp; Enabling support for 3D visualization in OpenCV; Creating OpenGL windows using OpenCV; Video capture using OpenCV; Rendering augmented reality; ARDrawingContext.hpp; ARDrawingContext.cpp; Demonstration; main.cpp.
Summary: 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. 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.
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Table of Contents; Mastering OpenCV with Practical Computer Vision Projects; Mastering OpenCV with Practical Computer Vision Projects; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Support files, eBooks, discount offers and more; Why Subscribe?; Free Access for Packt account holders; Preface; What this book covers; What you need for this book; Who this book is for; Conventions; Reader feedback; Customer support; Downloading the example code; Errata; Piracy; Questions; 1. Cartoonifier and Skin Changer for Android; Accessing the webcam.

Main camera processing loop for a desktop appGenerating a black-and-white sketch; Generating a color painting and a cartoon; Generating an ""evil"" mode using edge filters; Generating an ""alien"" mode using skin detection; Skin-detection algorithm; Showing the user where to put their face; Implementation of the skin-color changer; Porting from desktop to Android; Setting up an Android project that uses OpenCV; Color formats used for image processing on Android; Input color format from the camera; Output color format for display; Adding the cartoonifier code to the Android NDK app.

Reviewing the Android appCartoonifying the image when the user taps the screen; Saving the image to a file and to the Android picture gallery; Showing an Android notification message about a saved image; Changing cartoon modes through the Android menu bar; Reducing the random pepper noise from the sketch image; Showing the FPS of the app; Using a different camera resolution; Customizing the app; Summary; 2. Marker-based Augmented Reality on iPhone or iPad; Creating an iOS project that uses OpenCV; Adding OpenCV framework; Including OpenCV headers; Application architecture.

Accessing the cameraMarker detection; Marker identification; Grayscale conversion; Image binarization; Contours detection; Candidates search; Marker code recognition; Reading marker code; Marker location refinement; Placing a marker in 3D; Camera calibration; Marker pose estimation; Rendering the 3D virtual object; Creating the OpenGL rendering layer; Rendering an AR scene; Summary; References; 3. Marker-less Augmented Reality; Marker-based versus marker-less AR; Using feature descriptors to find an arbitrary image on video; Feature extraction; Definition of a pattern object.

Matching of feature pointsPatternDetector.cpp; Outlier removal; Cross-match filter; Ratio test; PatternDetector.cpp; Homography estimation; PatternDetector.cpp; Homography refinement; PatternDetector.cpp; Putting it all together; Pattern pose estimation; PatternDetector.cpp; Obtaining the camera-intrinsic matrix; Pattern.cpp; Application infrastructure; ARPipeline.hpp; ARPipeline.cpp; Enabling support for 3D visualization in OpenCV; Creating OpenGL windows using OpenCV; Video capture using OpenCV; Rendering augmented reality; ARDrawingContext.hpp; ARDrawingContext.cpp; Demonstration; main.cpp.

Summary.

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. 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.

Print version record.

Includes bibliographical references and index.

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