Motion detection and tracking

We will now build a sophisticated motion detection and tracking system with simple logic to find the difference between subsequent frames from a video feed, such as a webcam stream and plotting contours around the area where the difference is detected.

Let's import the required libraries and initialize the webcam:

import cv2
import numpy as np

cap = cv2.VideoCapture(0)

We will need a kernel for the dilation operation that we will create in advance rather than creating it every time in the loop:

k=np.ones((3,3),np.uint8)

The following code will capture and store the subsequent frames:

t0 = cap.read()[1]
t1 = cap.read()[1]

Now we initiate the while loop and calculate the difference between the frames and convert the output to grayscale for further processing:

while(True):
    
    d=cv2.absdiff(t1,t0)
    
    grey = cv2.cvtColor(d, cv2.COLOR_BGR2GRAY)

The output will be as follows, and it shows difference of pixels between the frames:

This image might contain some noise...