unleash the power of computer vision with Python using OpenCV /
First Statement of Responsibility
Joe Minichino, Joseph Howse.
EDITION STATEMENT
Edition Statement
Second edition.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Birmingham, UK :
Name of Publisher, Distributor, etc.
Packt Publishing,
Date of Publication, Distribution, etc.
[2015]
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource.
SERIES
Series Title
Community experience distilled
GENERAL NOTES
Text of Note
Includes index.
CONTENTS NOTE
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Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Setting Up OpenCV; Choosing and using the right setup tools; Installation on Windows; Using binary installers (no support for depth cameras); Using CMake and compilers; Installing on OS X; Using MacPorts with ready-made packages; Using MacPorts with your own custom packages; Using Homebrew with ready-made packages (no support for depth cameras); Using Homebrew with your own custom packages; Installation on Ubuntu and its derivatives
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Cameo -- an object-oriented designAbstracting a video stream with managers.CaptureManager; Abstracting a window and keyboard with managers.WindowManager; Applying everything with cameo.Cameo; Summary; Chapter 3: Processing Images with OpenCV 3; Converting between different color spaces; A quick note on BGR; The Fourier Transform; High pass filter; Low pass filter; Creating modules; Edge detection; Custom kernels -- getting convoluted; Modifying the application; Edge detection with Canny; Contour detection; Contours -- bounding box, minimum area rectangle, and minimum enclosing circle
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Contours -- convex contours and the Douglas-Peucker algorithmLine and circle detection; Line detection; Circle detection; Detecting shapes; Summary; Chapter 4: Depth Estimation and Segmentation; Creating modules; Capturing frames from a depth camera; Creating a mask from a disparity map; Masking a copy operation; Depth estimation with a normal camera; Object segmentation using the Watershed and GrabCut algorithms; Example of foreground detection with GrabCut; Image segmentation with the Watershed algorithm; Summary; Chapter 5: Detecting and Recognizing Faces; Conceptualizing Haar cascades
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Detecting features -- corners
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Getting Haar cascade dataUsing OpenCV to perform face detection; Performing face detection on a still image; Performing face detection on a video; Performing face recognition; Generating the data for face recognition; Recognizing faces; Preparing the training data; Loading the data and recognizing faces; Performing an Eigenfaces recognition; Performing face recognition with Fisherfaces; Performing face recognition with LBPH; Discarding results with confidence score; Summary; Chapter 6: Retrieving Images and Searching Using Image Descriptors; Feature detection algorithms; Defining features
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Using the Ubuntu repository (no support for depth cameras)Building OpenCV from a source; Installation on other Unix-like systems; Installing the Contrib modules; Running samples; Finding documentation, help, and updates; Summary; Chapter 2: Handling Files, Cameras, and GUIs; Basic I/O scripts; Reading/writing an image file; Converting between an image and raw bytes; Accessing image data with numpy.array; Reading/writing a video file; Capturing camera frames; Displaying images in a window; Displaying camera frames in a window; Project Cameo (face tracking and image manipulation)