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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 epipolar geometry?

Before discussing epipolar geometry, let's discuss what happens when we capture two images of the same scene from two different viewpoints. Consider the following figure:

What is epipolar geometry?

Let's see how it happens in real life. Consider the following image:

What is epipolar geometry?

Now, let's capture the same scene from a different viewpoint:

What is epipolar geometry?

Our goal is to match the keypoints in these two images to extract the scene information. The way we do this is by extracting a matrix that can associate the corresponding points between two stereo images. This is called the fundamental matrix.

As we saw in the camera figure earlier, we can draw lines to see where they meet. These lines are called epipolar lines. The point at which the epipolar lines converge is called epipole. If you match the keypoints using SIFT, and draw the lines towards the meeting point on the left image, it will look like this:

What is epipolar geometry?

Following are the matching feature points in the right image:

What is epipolar geometry?

The lines are epipolar lines. If you take the...

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