OpenCV Computer Vision Application Programming [Video]

OpenCV Computer Vision Application Programming [Video]

Sebastian Montabone

Incorporate OpenCV's powerful computer vision application programming techniques to build and make your own applications stand out from the crowd
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Video Details

ISBN 139781849694889
Course Length2 hours and 27 mins

Video Description

OpenCV (Open Source Computer Vision) is a library of programming functions that can be used for many applications such as augmented reality, robotics, surveillance, medical imaging, identification, to mention only a few. With OpenCV, developers can avoid the use of complex mathematics and algorithms and focus on developing applications, taking advantage of the comprehensive, ready to use functionality of OpenCV to automate tasks that a human performs visually. This course will expose you to the key concepts of OpenCV and enable you to build your own computer vision applications.

"OpenCV Computer Vision Application Programming" allows you to dive into the world of computer vision and get many practical benefits from it with minimal effort. You will learn to recognize and identify specific faces among others, or even train your very own object detector to use it for your own specific purposes.

"OpenCV Computer Vision Application Programming" helps you get started with the library by first learning how to install OpenCV correctly on your system. You will then explore basic image processing concepts as well as the different interfaces that you can use in OpenCV. Develop techniques to separate foreground and background in your images, create stunning panoramas easily by stitching normal images together, enhance your photographs, calibrate your camera and automatically detect common objects like faces or people on your images. Reduce the distortion of your photographs and make straight lines of the scene look straight instead of bent in your images.

You will learn to change the perspective of your images so that it appears that you are moving around, similar to google street view navigation and develop a 3D representation of a scene using stereoscopic images.

On completion of this course, you will be able to mix and match the provided examples to build your own application.

Style and Approach

Packt video courses are designed to cover the breadth of the topic in short, hands-on, task-based videos. Each course is divided into short manageable sections, so you can watch the whole thing or jump to the bit you need. The focus is on practical instructions and screencasts showing you how to get the job done.

This course shows results obtained on real images with suitable explanations accompanied with code that will facilitate your learning. Each example covers different aspects of computer vision that you can use in your own applications.

Table of Contents

Getting Started with OpenCV
Introduction to OpenCV
Installation on Linux
Installation on Windows
OpenCV Basics
OpenCV Interfaces
C Interface Basics
C++ Interface Basics
Python Interface Basics
Drawing Shapes
Image Processing
Blurring an Image
Understanding Image Morphology
Applying Geometric Transforms to an Image
Understanding Histograms
Segmenting Images and Obtaining Interesting Points
Clustering Data with k-means
Segmenting an Image using the watershed algorithm
Segmenting an Image Using the grabcut Algorithm
Finding and Matching Interesting Points
Computational Photography
Creating a Panorama
Removing Unwanted Objects
Enhancing Low Light Images
Working with HDR Images
Recognizing Objects
Detecting Shapes
Detecting Faces
Detecting People
Training your own detector
Recognizing faces
Calibration and Stereo Images
Calibrating the Camera
Undistorting an Image
Projecting an Image
Understanding Stereo Images
Generating a Depth Map

What You Will Learn

  • Learn what OpenCV is and how to install it on Linux and Windows
  • Development with OpenCV using the recommended C++ interface, as well as an introduction to the Python and C interfaces.
  • Segment objects in your images using grabcut and watershed, cluster your data, and spot interesting points in the image
  • Merge different images into a single panorama using the technique called panorama stitching
  • Detect common objects in your images, like faces, eyes, or people
  • Train your own object detector to detect custom objects
  • Recognize a face among many others
  • Learn to calibrate your camera
  • Remove or reduce the distortion of an image caused by the lens, commonly known as barrel distortion
  • Change the perspective of an image to match a different 3D pose
  • Create an image that represents depth information of the scene using stereoscopic images

Authors

Screenshots

Table of Contents

Getting Started with OpenCV
Introduction to OpenCV
Installation on Linux
Installation on Windows
OpenCV Basics
OpenCV Interfaces
C Interface Basics
C++ Interface Basics
Python Interface Basics
Drawing Shapes
Image Processing
Blurring an Image
Understanding Image Morphology
Applying Geometric Transforms to an Image
Understanding Histograms
Segmenting Images and Obtaining Interesting Points
Clustering Data with k-means
Segmenting an Image using the watershed algorithm
Segmenting an Image Using the grabcut Algorithm
Finding and Matching Interesting Points
Computational Photography
Creating a Panorama
Removing Unwanted Objects
Enhancing Low Light Images
Working with HDR Images
Recognizing Objects
Detecting Shapes
Detecting Faces
Detecting People
Training your own detector
Recognizing faces
Calibration and Stereo Images
Calibrating the Camera
Undistorting an Image
Projecting an Image
Understanding Stereo Images
Generating a Depth Map

Video Details

ISBN 139781849694889
Course Length2 hours and 27 mins
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