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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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 Joshi Joshi
Author Profile Icon Joshi
Joshi
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Table of Contents (19) Chapters Close

OpenCV with Python By Example
Credits
About the Author
About the Reviewers
www.PacktPub.com
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

Frame differencing


This is, possibly, the simplest technique we can use to see what parts of the video are moving. When we consider a live video stream, the difference between successive frames gives us a lot of information. The concept is fairly straightforward! We just take the difference between successive frames and display the differences.

If I move my laptop rapidly from left to right, we will see something like this:

If I rapidly move the TV remote in my hand, it will look something like this:

As you can see from the previous images, only the moving parts in the video get highlighted. This gives us a good starting point to see what areas are moving in the video. Here is the code to do this:

import cv2

# Compute the frame difference
def frame_diff(prev_frame, cur_frame, next_frame):
    # Absolute difference between current frame and next frame
    diff_frames1 = cv2.absdiff(next_frame, cur_frame)

    # Absolute difference between current frame and # previous frame
    diff_frames2 ...
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