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Practical Computer Vision

You're reading from Practical Computer Vision

Product type Book

Published in Feb 2018

Publisher Packt

ISBN-13 9781788297684

Pages 234 pages

Edition 1st Edition

Languages

Concepts

Computer Vision

Author (1):

Abhinav Dadhich

Table of Contents (12) Chapters

Preface

1. A Fast Introduction to Computer Vision

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

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Summary

In this appendix, we explained some prerequisites for computer vision algorithms. Linear algebraic expressions explained here are used in geometric modifications of image, such as translation, rotation, and so on.

Probabilistic approaches are used in a range of applications including, but not limited to, object detection, segmentation, and tracking applications. As such, having a good understanding of these prerequisites will make our application implementation faster and more efficient.

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Authors (1)

Abhinav Dadhich

Abhinav Dadhich is a Researcher and Application Developer on deep learning at Abeja Inc. Tokyo. His day is often filled with designing deep learning models for computer vision applications like image classification, object detection, segmentation etc. His passion lies in understanding and replicating human vision system. Previously, he has worked on 3D mapping and robot navigation. He has graduated with B.Tech. in EE from IIT Jodhpur, India and has done his M.Eng. in Information Science from NAIST, Japan. He puts up notes and codes for several topics on GitHub profile.

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