OpenCV 3 - Advanced Image Detection and Reconstruction [Video]

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OpenCV 3 - Advanced Image Detection and Reconstruction [Video]

Robert Laganiere

2 customer reviews
Videos to help you build computer vision applications that make the most of the popular C++ library, OpenCV 3

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Video Details

ISBN 139781788391184
Course Length1 hour 30 minutes

Video Description

Making your applications see has never been easier with OpenCV. With it, you can teach your robot how to follow your cat, write a program to correctly identify the members of One Direction, or even help you find the right colors for your redecoration. OpenCV 3 Computer Vision Application Programming Solutions provides a complete introduction to the OpenCV library and explains how to build your first computer vision program. You will be presented with a variety of computer vision algorithms, and exposed to important concepts in image and video analysis, which will enable you to build your own computer vision applications.

This video helps you to get started with the OpenCV library, and shows you how to install and deploy it to write effective computer vision applications following good programming practices. You will learn how to read and write images and manipulate their pixels. Different techniques for image enhancement and shape analysis will be presented. You will learn how to detect specific image features such as lines, circles, or corners. You will be introduced to the concepts of mathematical morphology and image filtering.

Style and Approach

This video will arm you with the basics you need to start writing world-aware applications right from the pixel level all the way through to processing video sequences.

Table of Contents

Detecting Interest Points
The Course Overview
Detecting Corners in an Image
Detecting Features Quickly
Detecting Scale-Invariant Features
Detecting FAST Features at Multiple Scales
Describing and Matching Interest Points
Matching Local Templates
Describing and Matching Local Intensity Patterns
Matching Keypoints with Binary Descriptors
Estimating Projective Relations in Images
Computing the Fundamental Matrix of an Image Pair
Matching Images Using Random Sample Consensus
Computing a Homography Between Two Images
Detecting a Planar Target in Images
Learning from Examples
Recognizing Faces Using Nearest Neighbors
Finding Objects and Faces with a Cascade of Haar Features
Detecting Objects and People with Support Vector Machines

What You Will Learn

  • Calibrate the camera from different image observations
  • Detect people and objects in images using machine learning techniques
  • Reconstruct a 3D scene from images

Authors

Table of Contents

Detecting Interest Points
The Course Overview
Detecting Corners in an Image
Detecting Features Quickly
Detecting Scale-Invariant Features
Detecting FAST Features at Multiple Scales
Describing and Matching Interest Points
Matching Local Templates
Describing and Matching Local Intensity Patterns
Matching Keypoints with Binary Descriptors
Estimating Projective Relations in Images
Computing the Fundamental Matrix of an Image Pair
Matching Images Using Random Sample Consensus
Computing a Homography Between Two Images
Detecting a Planar Target in Images
Learning from Examples
Recognizing Faces Using Nearest Neighbors
Finding Objects and Faces with a Cascade of Haar Features
Detecting Objects and People with Support Vector Machines

Video Details

ISBN 139781788391184
Course Length1 hour 30 minutes
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