What you will need to do is: Calculate the absolute difference...

What you will need to do is:

Calculate the absolute difference frame between two frames as the camera is capturing frames

and threshold them with a specific value e.g. 20. Save the output abs. diff. frame in a video file.

Try for example to move your hands in front of the camera while capturing and analyzing the

frames. You should be able to visually identify well the contour of your hands when these are

moving but not so much when they are staying still.

This part continues from our previous demo with capturing frames from the camera using

load_camera.py

The load_camera.py:

# Load opencv module

import cv2

# Creat a VideoCapture object

cap = cv2.VideoCapture(0)

# Check if camera opened successfully

if (cap.isOpened() is False):

print("Unable to read camera feed")

# Default resolutions of the frame are obtained.

# The default resolutions

# are system dependent.

# We convert the resolutions from float to integer.

frame_width = int(cap.get(3))

frame_height = int(cap.get(4))

# Define the codec and create VideoWriter object. The output is

# stored in 'output.avi' file.

out = cv2.VideoWriter('output.avi',

cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'),

10, (frame_width,frame_height))

while(True):

ret, frame = cap.read()

if ret:

# color to grayscale

# Write the frame into the file 'output.avi'

out.write(frame)

print(frame.dtype)

print(frame.shape)

# Display the resulting frame

cv2.imshow('frame', frame)

# Press Q on keyboard to stop recording

if cv2.waitKey(1) & 0xFF == ord('q'):

break

# Break the loop

else:

break

# When everything done,

# release the video capture and write objects

cap.release()

out.release()

# Closes all the frames

cv2.destroyAllWindows()