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1. |
Record Nr. |
UNINA990002585650403321 |
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Titolo |
Indagine sul fenomeno del contrabbando di tabacchi a Napoli / ricerca coordinata e diretta da A. Fossati e N. C. Lauro ; Guardia di Finanza, Comando Zona Meridionale Tirrenica ; Università degli Studi Federico 2. Facoltà di economia e commercio |
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Pubbl/distr/stampa |
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Descrizione fisica |
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Disciplina |
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Locazione |
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MAS |
FLFBC |
DECLI |
SES |
DECTS |
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Collocazione |
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XXX-F-49 |
XXX-F-50 |
364.133 IND 1 |
519 FOS |
F/1 LAU |
K3-K4.529 |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNINA9910786068403321 |
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Autore |
Lelis Baggio Daniel |
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Titolo |
Mastering OpenCV with practical computer vision projects [[electronic resource] /] / Daniel Lelis Baggio ... [et al.] |
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Pubbl/distr/stampa |
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Birmingham, UK : , : Packt Pub., , 2012 |
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ISBN |
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1-62198-906-2 |
1-299-14864-6 |
1-84951-783-5 |
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Edizione |
[First edition] |
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Descrizione fisica |
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1 online resource (340 pages) |
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Disciplina |
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Soggetti |
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C++ (Computer program language) |
Computer vision |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1:Cartoonifier and Skin Changer for Android; Accessing the webcam; Main camera processing loop for a desktop app; Generating 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 OpenCVColor 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 app; Cartoonifying 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 appSummary; Chapter 2:Marker-based Augmented |
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Reality on iPhone or iPad; Creating an iOS project that uses OpenCV; Adding OpenCV framework; Including OpenCV headers; Application architecture; Marker 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 |
Chapter 3:Marker-less Augmented RealityMarker-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 points; PatternDetector.cpp; Outlier removal; Cross-match filter; Ratio test; Homography estimation; Homography refinement; 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 OpenCVVideo capture using OpenCV; Rendering augmented reality; ARDrawingContext.hpp; ARDrawingContext.cpp; Demonstration; main.cpp; Summary; References; Chapter 4:Exploring Structure from Motion Using OpenCV; Structure from Motion concepts; Estimating the camera motion from a pair of images; Point matching using rich feature descriptors; Point matching using optical flow; Finding camera matrices; Reconstructing the scene; Reconstruction from many views; Refinement of the reconstruction; Visualizing 3D point clouds with PCL; Using the example code; Summary |
References |
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Sommario/riassunto |
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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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