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Frame Difference based tracker stuck with first frame

So I have been working these last few weeks on detecting and tracking motion on a video. My purpose is simple, detecting a dog once he moves and tracking it (with a rectangle box surrounding it). I only want to track one motion (the dog's) ignoring any other motion. After many unsuccessful trials with object and motion tracking algorithms and codes using Opencv, I came across something that I was able to modify to get closer to my goal. The only issue is that the code seems to keep the information from the first frame during the whole video, which causes the code to detect and put a rectangle in an empty area ignoring the actual motion.

Here's the code I'm using:

import imutils
import time
import cv2

previousFrame = None

def searchForMovement(cnts, frame, min_area):

    text = "Undetected"
    flag = 0

    for c in cnts:
        # if the contour is too small, ignore it
        if cv2.contourArea(c) < min_area:
            continue

        #Use the flag to prevent the detection of other motions in the video
        if flag == 0:
            (x, y, w, h) = cv2.boundingRect(c)

            #print("x y w h")
            #print(x,y,w,h) 
            cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
            text = "Detected"
            flag = 1

    return frame, text

def trackMotion(ret,frame, gaussian_kernel, sensitivity_value, min_area):

    if ret:

        # Convert to grayscale and blur it for better frame difference
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        gray = cv2.GaussianBlur(gray, (gaussian_kernel, gaussian_kernel), 0)

        global previousFrame

        if previousFrame is None:
            previousFrame = gray
            return frame, "Uninitialized", frame, frame   

        frameDiff = cv2.absdiff(previousFrame, gray)
        thresh = cv2.threshold(frameDiff, sensitivity_value, 255, cv2.THRESH_BINARY)[1]

        thresh = cv2.dilate(thresh, None, iterations=2)
        _, cnts, _ = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

        frame, text = searchForMovement(cnts, frame, min_area)
        #previousFrame = gray

    return frame, text, thresh, frameDiff       


if __name__ == '__main__':

    video = "Track.avi"
    video0 = "Track.mp4"
    video1= "Ntest1.avi"
    video2= "Ntest2.avi"

    camera = cv2.VideoCapture(video1)
    time.sleep(0.25)
    min_area = 5000 #int(sys.argv[1])

    cv2.namedWindow("Security Camera Feed")

    while camera.isOpened():

        gaussian_kernel = 27
        sensitivity_value = 5
        min_area = 2500

        ret, frame = camera.read()

        #Check if the next camera read is not null
        if ret:
            frame, text, thresh, frameDiff = trackMotion(ret,frame, gaussian_kernel, sensitivity_value, min_area)

        else:
            print("Video Finished")
            break

        cv2.namedWindow('Thresh',cv2.WINDOW_NORMAL)
        cv2.namedWindow('Frame Difference',cv2.WINDOW_NORMAL)
        cv2.namedWindow('Security Camera Feed',cv2.WINDOW_NORMAL)

        cv2.resizeWindow('Thresh', 800,600)
        cv2.resizeWindow('Frame Difference', 800,600)
        cv2.resizeWindow('Security Camera Feed', 800,600)
      # uncomment to see the tresh and framedifference displays                  
        cv2.imshow("Thresh", thresh)
        cv2.imshow("Frame Difference", frameDiff)

        cv2.putText(frame, text, (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
        cv2.imshow("Security Camera Feed", frame)

        key = cv2.waitKey(3) & 0xFF
        if key == 27 or key == ord('q'):
            print("Bye")
            break

    camera.release()
cv2.destroyAllWindows()

The following pictures show the problems I run into. Both Threshold and Frame difference keep displaying a result in the area where the dog was in the first frame, even after the dog is completely out of it. When I limit the tracking to only 1 motion, it starts ignoring the actual motion and keeps detecting that same area from the first frame.

image description

Second picture:

image description

I hope someone can help me solve this issue or suggest a better approach maybe.

Thanks a lot !!

Frame Difference based tracker stuck with first frame

Here's the code I'm using:

import imutils
import time
import cv2

previousFrame = None
count = 0
test = 0
temp_frame = None
rect = None

def searchForMovement(cnts, frame, min_area):

    global rect
    text = "Undetected"
    flag = 0

    for c in cnts:
        # if the contour is too small, ignore it
        if cv2.contourArea(c) < min_area:
            continue
        #print(c)

        #Use the flag to prevent the detection of other motions in the video
        if flag == 0:
            (x, y, w, h) = cv2.boundingRect(c)
             x = x - 100
            y = y - 100
            w = 400
            h = 400
            #print("x y w h")
            #print(x,y,w,h) 
            cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
            text = "Detected"
            rect = c
            flag = 1

    if text == "Undetected":
        (x, y, w, h) = cv2.boundingRect(rect)
        x = x - 100
        y = y - 100
        w = 400
        h = 400
        cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
        text = "Detected"



    if text == "Undetected":
        print (text, temp_frame)


    return frame, text

def trackMotion(ret,frame, gaussian_kernel, sensitivity_value, min_area):

    if ret:

        # Convert to grayscale and blur it for better frame difference
        # frame = cv2.bilateralFilter(frame, 7, 150, 150)
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        gray = cv2.GaussianBlur(gray, (gaussian_kernel, gaussian_kernel), 0)

         global previousFrame
        global count
        global test
        global temp_frame

        if previousFrame is None:
            previousFrame = gray
            return frame, "Uninitialized", frame, frame   

        frameDiff = cv2.absdiff(previousFrame, gray)
        thresh = cv2.threshold(frameDiff, sensitivity_value, 255, cv2.THRESH_BINARY)[1]

        thresh = cv2.dilate(thresh, None, iterations=2)
        _, cnts, _ = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

        frame, text = searchForMovement(cnts, frame, min_area)
        #previousFrame 


        if text == "Detected":
            temp_frame = frame

        else:
            frame = temp_frame


        if text == "Undetected":
            print (text, temp_frame)


        if count % 10 == 0:
            previousFrame = gray

        count = count + 1

    return frame, text, thresh, frameDiff       


if __name__ == '__main__':

    video = "Track.avi"
    video0 = video0= "Track.mp4"
    video1= "Ntest1.avi"
    video2= "Ntest2.avi"

    camera = cv2.VideoCapture(video1)
cv2.VideoCapture(video2)
    time.sleep(0.25)
    min_area = 5000 #int(sys.argv[1])

    cv2.namedWindow("Security Camera Feed")
 
    while camera.isOpened():

        gaussian_kernel = 27
        sensitivity_value = 5
        min_area = 2500

        ret, frame = camera.read()

        #Check if the next camera read is not null
        if ret:
            frame, text, thresh, frameDiff = trackMotion(ret,frame, gaussian_kernel, sensitivity_value, min_area)

         else:
            print("Video Finished")
            close = False
            while not close:
                key1 = cv2.waitKey(3) & 0xFF
                if key1 == 27 or key1 == ord('q'):
                    close = True

            break

        cv2.namedWindow('Thresh',cv2.WINDOW_NORMAL)
        cv2.namedWindow('Frame Difference',cv2.WINDOW_NORMAL)
        cv2.namedWindow('Security Camera Feed',cv2.WINDOW_NORMAL)

        cv2.resizeWindow('Thresh', 800,600)
        cv2.resizeWindow('Frame Difference', 800,600)
        cv2.resizeWindow('Security Camera Feed', 800,600)
      # uncomment to see the tresh and framedifference displays                  
        cv2.imshow("Thresh", thresh)
        cv2.imshow("Frame Difference", frameDiff)

        cv2.putText(frame, text, (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
        cv2.imshow("Security Camera Feed", frame)

        key = cv2.waitKey(3) & 0xFF
        if key == 27 or key == ord('q'):
            print("Bye")
            break

    camera.release()
 cv2.destroyAllWindows()

image description

Second picture:

image description

I hope someone can help me solve this issue or suggest a better approach maybe.

Thanks a lot !!

EDIT:

The answer given Tetragramm helped solve the issue. The ghosting is gone and the box follows every action detected. It did cause other issues (not detecting action when the dog stops for a bit, and focusing the box on parts of the body that move not the whole body) but I changed it to make the subtracted frame updated every 10 frames instead and I worked a simple trick to keep the rectangle in the last place the action was detected when the current frame has no action detected (it solves the no detection problem).

The only problem I need to solve is the box focusing on body parts. Is there a way to make it ignore those small movements to only move the boundaries box when the whole body moves ?

Thank you !!