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OpenCV with Python By Example

You're reading from   OpenCV with Python By Example Build real-world computer vision applications and develop cool demos using OpenCV for Python

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Product type Paperback
Published in Sep 2015
Publisher Packt
ISBN-13 9781785283932
Length 296 pages
Edition 1st Edition
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Author (1):
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Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Table of Contents (14) Chapters Close

Preface 1. Applying Geometric Transformations to Images FREE CHAPTER 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

What is stereo correspondence?

When we capture images, we project the 3D world around us on a 2D image plane. So technically, we only have 2D information when we capture those photos. Since all the objects in that scene are projected onto a flat 2D plane, the depth information is lost. We have no way of knowing how far an object is from the camera or how the objects are positioned with respect to each other in the 3D space. This is where stereo vision comes into the picture.

Humans are very good at inferring depth information from the real world. The reason is that we have two eyes positioned a couple of inches from each other. Each eye acts as a camera and we capture two images of the same scene from two different viewpoints, that is, one image each using the left and right eyes. So, our brain takes these two images and builds a 3D map using stereo vision. This is what we want to achieve using stereo vision algorithms. We can capture two photos of the same scene using different viewpoints...

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