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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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Dataset and libraries

In this chapter, we will be using OpenCV for most of the applications. In the last section, for Visual Simultaneous Localization and Mapping (vSLAM) techniques, we will see the use of an open source repository; directions for its use are mentioned in the section. The dataset is the RGBD dataset, consisting of a sequence of images captured using RGB and a depth camera. To download this dataset, visit the following link and download the fr1/xyz tar file: https://vision.in.tum.de/data/datasets/rgbd-dataset/download.

Alternatively, use the following (Linux only) command in a Terminal:

wget https://vision.in.tum.de/rgbd/dataset/freiburg1/rgbd_dataset_freiburg1_xyz.tgz
tar -xvf rgbd_dataset_freiburg1_xyz.tgz

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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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