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OpenCV 3.x with Python By Example - Second Edition

You're reading from  OpenCV 3.x with Python By Example - Second Edition

Product type Book
Published in Jan 2018
Publisher Packt
ISBN-13 9781788396905
Pages 268 pages
Edition 2nd Edition
Languages
Authors (2):
Gabriel Garrido Calvo Gabriel Garrido Calvo
Profile icon Gabriel Garrido Calvo
Prateek Joshi Prateek Joshi
Profile icon Prateek Joshi
View More author details
Toc

Table of Contents (17) Chapters close

Title Page
Copyright and Credits
Contributors
Packt Upsell
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. Seam Carving 7. Detecting Shapes and Segmenting an Image 8. Object Tracking 9. Object Recognition 10. Augmented Reality 11. Machine Learning by an Artificial Neural Network 1. Other Books You May Enjoy

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 we move rapidly from left to right, we will see something like this:

As you can see from the previous image, 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 = cv2.absdiff(cur_frame, prev_frame) 

    # Return the result of bitwise 'AND...
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