| Document Type
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BL
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| Record Number
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855968
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| Main Entry
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Minichino, Joe.
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| Title & Author
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Learning OpenCV 3 computer vision with Python : : unleash the power of computer vision with Python using OpenCV /\ Joe Minichino, Joseph Howse.
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| Edition Statement
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Second edition.
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| Publication Statement
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Birmingham, UK :: Packt Publishing,, [2015]
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| Series Statement
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Community experience distilled
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| Page. NO
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1 online resource.
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| ISBN
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1785289772
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: 9781785289774
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1785283847
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9781785283840
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| Notes
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Includes index.
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| Contents
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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)
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| Subject
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Computer vision.
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| Subject
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Python (Computer program language)
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| Subject
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Computer vision.
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| Subject
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COMPUTERS-- General.
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| Subject
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Python (Computer program language)
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| Dewey Classification
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006.3/7
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| LC Classification
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TA1634
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| Added Entry
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Howse, Joseph.
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