Motion Detection using OpenCV

This python program will allow you to detect motion and also store the time interval of the motion :

click here to see video

Requirements:

1. Python3
2. OpenCV (library)
3. Numpy (library)

Main Logic : 

             Videos can be treated as stack of pictures called frames. Here i am comparing current frame(Image) to the last frame(Image) which should be static(No movements initially). We compare two images by comparing the intensity value of each pixels. In python we can do it easily as you can see in following code:

Code :

# import cv2 and numpy

import cv2

import numpy as np

# capturing video

cap = cv2.VideoCapture('video.mp4')

# reading back-to-back frames(images) from video

ret, frame1 = cap.read()

ret, frame2 = cap.read()

while cap.isOpened():

       # Difference between frame1(image) and frame2(image)

       diff = cv2.absdiff(frame1, frame2)

       # Converting color image to gray_scale image

       gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)

       # Converting gray scale image to GaussianBlur, so that change can be find easily 

       blur = cv2.GaussianBlur(gray, (5, 5), 0)

       # If pixel value is greater than 20, it is assigned white(255) otherwise black

       _, thresh = cv2.threshold(blur, 20, 255, cv2.THRESH_BINARY)

       dilated = cv2.dilate(thresh, None, iterations=4)

       # finding contours of moving object

       contours, hirarchy = cv2.findContours(dilated, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

       # making rectangle around moving object

       for contour in contours:

              (x, y, w, h) = cv2.boundingRect(contour)

              if cv2.contourArea(contour) < 700:

                     continue

              cv2.rectangle(frame1, (x, y), (x+w, y+h), (0, 255, 255), 2)

       # Display original frame

       cv2.imshow('Motion Detector', frame1)

       # Display Diffrenciate Frame

       cv2.imshow('Difference Frame', thresh)

       # Assign frame2(image) to frame1(image)

       frame1 = frame2

       #Read new frame2

       ret, frame2 = cap.read()

       # Press 'esc' for quit 

       if cv2.waitKey(40) == 27:

              break

# Release cap resource

cap.release()

# Destroy all windows

cv2.destroyAllWindows()

click here to see video