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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

Applications

While deep learning can extract good features for high-level applications, there are areas that require pixel level matching to compute geometric information from an image. Some of the applications that use this information are:

  • Drones: In commercial robots like drones, the image sequence is used to compute the motion of the camera mounted on them. This helps them to make robust motion estimations and, in addition to other Inertial Measurement Units (IMU) such as gyroscopes, accelerometers, and so on, the overall motion is estimated more accurately.
  • Image editing applications: Smartphones and professional applications for image editing include tools like panorama creation, image stitching, and so on. These apps compute orientation from common pixels across image samples and align the images in one target orientation. The resulting image looks as if it has been stitched...
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