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OpenCV with Python By Example

You're reading from  OpenCV with Python By Example

Product type Book
Published in Sep 2015
Publisher Packt
ISBN-13 9781785283932
Pages 296 pages
Edition 1st Edition
Languages
Author (1):
Prateek Joshi Prateek Joshi
Profile icon Prateek Joshi

Table of Contents (19) Chapters

OpenCV with Python By Example
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. Applying Geometric Transformations to Images 2. Detecting Edges and Applying Image Filters 3. Cartoonizing an Image 4. Detecting and Tracking Different Body Parts 5. Extracting Features from an Image 6. Creating a Panoramic Image 7. Seam Carving 8. Detecting Shapes and Segmenting an Image 9. Object Tracking 10. Object Recognition 11. Stereo Vision and 3D Reconstruction 12. Augmented Reality Index

How to augment our reality?


Now that we know how to track planar objects, let's see how to overlay 3D objects on top of the real world. The objects are 3D but the video on our screen is 2D. So the first step here is to understand how to map those 3D objects to 2D surfaces so that it looks realistic. We just need to project those 3D points onto planar surfaces.

Mapping coordinates from 3D to 2D

Once we estimate the pose, we project the points from the 3D to the 2D. Consider the following image:

As we can see here, the TV remote control is a 3D object but we are seeing it on a 2D plane. Now if we move it around, it will look like this:

This 3D object is still on a 2D plane. The object has moved to a different location and the distance from the camera has changed as well. How do we compute these coordinates? We need a mechanism to map this 3D object onto the 2D surface. This is where the 3D to 2D projection becomes really important.

We just need to estimate the initial camera pose to start with...

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