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Practical Computer Vision

You're reading from   Practical Computer Vision Extract insightful information from images using TensorFlow, Keras, and OpenCV

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788297684
Length 234 pages
Edition 1st Edition
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Author (1):
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Abhinav Dadhich Abhinav Dadhich
Author Profile Icon Abhinav Dadhich
Abhinav Dadhich
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Table of Contents (12) Chapters Close

Preface 1. A Fast Introduction to Computer Vision FREE CHAPTER 2. Libraries, Development Platform, and Datasets 3. Image Filtering and Transformations in OpenCV 4. What is a Feature? 5. Convolutional Neural Networks 6. Feature-Based Object Detection 7. Segmentation and Tracking 8. 3D Computer Vision 9. Mathematics for Computer Vision 10. Machine Learning for Computer Vision 11. Other Books You May Enjoy

Summary

In this chapter, the aim was to view computer vision from a geometrical point of view. Starting with understanding how an image is formed using a pinhole camera, there was a discussion on how to incorporate three-dimensional worlds using multi-image formation. We saw an explanation of Visual Odometry with an introduction to Visual SLAM. The various steps involved in SLAM were explained and a demo of using ORB-SLAM was also shown, so that we could see a SLAM operation as it happened. This is basic motivation to extend the SLAM solution for various other datasets, and so create interesting applications.

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