load_camera-1.py:

# Load opencv module import cv2 # Create 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()

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