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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

Visual odometry

Odometry is the process of incrementally estimating the position of a robot or device. In the case of a wheeled robot, it uses wheel motion or inertial measurement using tools such as gyroscopes or accelerometers to estimate the robot's position by summing over wheel rotations. Using visual odometry (VO), we can estimate the odometry of cameras using only image sequences by continuously estimating camera motion.

A major use of VO is in autonomous robots like drones, where gyroscopes and accelerometers are not robust enough for motion estimation. However, there are several assumptions and challenges in using VO:

  • Firstly, objects in the scene for the camera should be static. While the camera captures a sequence of the image, the only moving object should be the camera itself.
  • Moreover, during the estimation of VO, if there are significant illumination changes...
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