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OpenCV: Computer Vision Projects with Python

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Title: OpenCV: Computer Vision Projects with Python
Description: About This BookUse OpenCV's Python bindings to capture video, manipulate images, and track objectsLearn about the different functions of OpenCV and their actual implementations.Develop a series of intermediate to advanced projects using OpenCV and PythonWho This Book Is ForThis learning path is for someone who has a working knowledge of Python and wants to try out OpenCV. This Learning Path will take you from a beginner to an expert in computer vision applications using OpenCV. OpenCV's application are humongous and this Learning Path is the best resource to get yourself acquainted thoroughly with OpenCV.What You Will LearnInstall OpenCV and related software such as Python, NumPy, SciPy, OpenNI, and SensorKinect - all on Windows, Mac or UbuntuApply'curves'and other color transformations to simulate the look of old photos, movies, or video gamesApply geometric transformations to images, perform image filtering, and convert an image into a cartoon-like imageRecognize hand gestures in real time and perform hand-shape analysis based on the output of a Microsoft Kinect sensorReconstruct a 3D real-world scene from 2D camera motion and common camera reprojection techniquesDetect and recognize street signs using a cascade classifier and support vector machines (SVMs)Identify emotional expressions in human faces using convolutional neural networks (CNNs) and SVMsStrengthen your OpenCV2 skills and learn how to use new OpenCV3 featuresIn DetailOpenCV is a state-of-art computer vision library that allows a great variety of image and video processing operations. OpenCV for Python enables us to run computer vision algorithms in real time. This learning path proposes to teach the following topics. First, we will learn how to get started with OpenCV and OpenCV3's Python API, and develop a computer vision application that tracks body parts. Then, we will build amazing intermediatelevel computer vision applications such as making an object disappear from an image, identifying different shapes, reconstructing a 3D map from images, and building an augmented reality application, Finally, we'll move to more advanced projects such as hand gesture recognition, tracking visually salient objects, as well as recognizing traffic signs and emotions on faces using support vector machines and multi-layer perceptrons respectively.This learning path is for someone who has a working knowledge of Python and wants to try out OpenCV. This Learning Path will take you from a beginner to an expert in computer vision applications using OpenCV.OpenCV's application are humongous and this Learning Path is the best resource to get yourself acquainted thoroughly with OpenCV.
Authors: Joseph Howse, Prateek Joshi, Michael Beyeler
Resource Type: eBook.
Subjects: Computer vision, Image processing, Python (Computer program language)
Categories: COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition
Database: eBook Collection (EBSCOhost)
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  Data: About This BookUse OpenCV's Python bindings to capture video, manipulate images, and track objectsLearn about the different functions of OpenCV and their actual implementations.Develop a series of intermediate to advanced projects using OpenCV and PythonWho This Book Is ForThis learning path is for someone who has a working knowledge of Python and wants to try out OpenCV. This Learning Path will take you from a beginner to an expert in computer vision applications using OpenCV. OpenCV's application are humongous and this Learning Path is the best resource to get yourself acquainted thoroughly with OpenCV.What You Will LearnInstall OpenCV and related software such as Python, NumPy, SciPy, OpenNI, and SensorKinect - all on Windows, Mac or UbuntuApply'curves'and other color transformations to simulate the look of old photos, movies, or video gamesApply geometric transformations to images, perform image filtering, and convert an image into a cartoon-like imageRecognize hand gestures in real time and perform hand-shape analysis based on the output of a Microsoft Kinect sensorReconstruct a 3D real-world scene from 2D camera motion and common camera reprojection techniquesDetect and recognize street signs using a cascade classifier and support vector machines (SVMs)Identify emotional expressions in human faces using convolutional neural networks (CNNs) and SVMsStrengthen your OpenCV2 skills and learn how to use new OpenCV3 featuresIn DetailOpenCV is a state-of-art computer vision library that allows a great variety of image and video processing operations. OpenCV for Python enables us to run computer vision algorithms in real time. This learning path proposes to teach the following topics. First, we will learn how to get started with OpenCV and OpenCV3's Python API, and develop a computer vision application that tracks body parts. Then, we will build amazing intermediatelevel computer vision applications such as making an object disappear from an image, identifying different shapes, reconstructing a 3D map from images, and building an augmented reality application, Finally, we'll move to more advanced projects such as hand gesture recognition, tracking visually salient objects, as well as recognizing traffic signs and emotions on faces using support vector machines and multi-layer perceptrons respectively.This learning path is for someone who has a working knowledge of Python and wants to try out OpenCV. This Learning Path will take you from a beginner to an expert in computer vision applications using OpenCV.OpenCV's application are humongous and this Learning Path is the best resource to get yourself acquainted thoroughly with OpenCV.
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      – Code: 006.37
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Computer vision
        Type: general
      – SubjectFull: Image processing
        Type: general
      – SubjectFull: Python (Computer program language)
        Type: general
    Titles:
      – TitleFull: OpenCV: Computer Vision Projects with Python
        Type: main
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          Name:
            NameFull: Joseph Howse
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          Name:
            NameFull: Prateek Joshi
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            NameFull: Michael Beyeler
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            NameFull: Joseph Howse
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            NameFull: Prateek Joshi
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            NameFull: Michael Beyeler
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2016
            – D: 09
              M: 05
              Type: profile
              Y: 2017
          Identifiers:
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              Value: 9781787125490
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              Value: 9781787123847
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            – TitleFull: OpenCV: Computer Vision Projects with Python
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