OpenCV Computer Vision Application Programming [Video]

Sebastian Montabone

OpenCV Computer Vision Application Programming [Video]
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  • New! Packt Video courses: practical screencast-based tutorials that show you how to get the job done. Bite sized chunks, hands on instructions, and powerful results.
  • Learn everything you need to get started with OpenCV
  • Contains many practical examples covering different areas of computer vision that can be mixed and matched to build your own application
  • Packed with code with relevant explanation to demonstrate real results from real images

Video Details

Language : English
Release Date : Thursday, May 30, 2013
Course Length : 2 hours and 27 mins
ISBN : 1849694885
ISBN 13 : 9781849694889
Author(s) : Sebastian Montabone
Topics and Technologies : All Books, Application Development, Video, Open Source

Table of Contents

  1. Getting Started with OpenCV [19:54 minutes]
    • Introduction to OpenCV
    • Installation on Linux.
    • Installation on Windows

  2. OpenCV Basics [25:16 minutes]
    • OpenCV Interfaces
    • C Interface Basics
    • C++ Interface Basics
    • Python Interface Basics
    • Drawing Shapes

  3. Image Processing [19:25 mins]
    • Blurring an Image
    • Understanding Image Morphology
    • Applying Geometric Transforms
    • Understanding Histograms

  4. Segmenting Images and Obtaining Interesting Points [23:07 mins]
    • Clustering data with k-means
    • Segmenting an image using the watershed algorithm
    • Segmenting an image using the grabcut algorithm
    • Finding and matching interesting points

  5. Computational Photography [11:16 mins]
    • Creating a panorama
    • Removing unwanted objects
    • Enhancing low light photographs
    • Working with HDR images

  6. Recognizing Objects [26:25 mins]
    • Detecting shapes
    • Detecting faces
    • Detecting people
    • Training your own detector
    • Recognizing faces

  7. Calibration and Stereo Images [22:04 mins]
    • Calibrating your camera
    • Undistorting an Image
    • Projecting an Image
    • Understanding Stereo Images
    • Generating a Depth Map

 

 

Sebastian Montabone

Sebastian Montabone is a computer engineer with a Master of Science degree in computer vision. He is the author of scientific articles regarding image processing and a book, Beginning Digital Image Processing: Using Free Tools for Photographers. He uses many open source software and strongly believes in the open source philosophy. Embedded systems also have been of interest to him, especially mobile phones. He created and taught a course about development of applications for mobile phones, and has been recognized as a Nokia developer champion. If you could summarize all his areas of interest in a single concept, it would be ubiquitous computing. Currently he is a software consultant and entrepreneur. You can visit his blog at http://www.samontab.com where he shares his current projects with the world.
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What you will learn from this video course

  • 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

Who this video course is for

If you are a novice or expert C++ programmer who wants to learn how to use the OpenCV library to develop computer vision applications in ways such as augmented reality, robotics, surveillance, computational photography, object detection or identification then this course is for you. Prior knowledge of computer vision or image processing is not needed.

In Detail

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.

 

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.

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