How to detect human using findcontours based on the human shape?

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I tried this CPP code and adopt it to Java side as below. I changed some of the lines because no need of them. So, the last state of it with Java goes here. I used *.mp4 file but i resize the frame before processing because more than a 640x480 resolution, processing is too slow. I prefer to dynamic resize the frame to 320x240 or max. 640x480 before processing :

// Fields...

 Mat fg;     
 Mat blurred;
 Mat thresholded;
 Mat gray;
 Mat blob;
 Mat bgmodel;                                            

 BackgroundSubtractorMOG2 bgs;      

 List<MatOfPoint> contours = new ArrayList<MatOfPoint>();            

 CascadeClassifier body;

// Initializer part (you may put it to a private method and call it from constructor)...

     bgs = new BackgroundSubtractorMOG2();
     bgs.setInt("nmixtures", 3);
     bgs.setInt("history", 1000);
     bgs.setInt("varThresholdGen", 15);
     //bgs.setBool("bShadowDetection", true);   // This feautee does not exist on OpenCV-2.4.11
     bgs.setInt("nShadowDetection",0);                               
     bgs.setDouble("fTau", 0.5);                                         

     body=new CascadeClassifier("mapbase/hogcascade_pedestrians.xml"); // Standart sample pedestrian trained data file
      if(body.empty())  
      {  
           System.out.println("--(!)Error loading hogcascade file\n");  
            return;  
      }  
      else  
      {  
                 System.out.println("Pedestrian classifier loaded up");  
      }

// Frame reader part...

VideoCapture cam = new VideoCapture("D:\\Sample_Videos\\pedestrian-much.mp4"); // int 0 : Webcam, String : rtsp://IP:PORT/PATH for ip camera etc.
        if(cam.isOpened())  
          {  
           Thread.sleep(500); /// This one-time delay allows the Webcam to initialize itself  
           while( true )  
           {  
             cam.read(cam_image);  
             if(!cam_image.empty())  
              {            
                   // Thread.sleep(50); // If too much computation, you may give a time to CPU        
                   Imgproc.resize(cam_image, resizeImage, new Size(320, 240));
                   //Apply the classifier to the captured image  
                   renderImage=faceDetector.detect(resizeImage);
                   //Display the image  
                   BufferedImage img = facePanel.matToBufferedImage(renderImage);
                   facePanel.repaint();
                   renderImage.release();
              }  
              else  
              {   
                   System.out.println(" --(!) No captured frame from video source!");
                   break;   
              }  
             }  
            }
           cam.release(); //release the webcam   }

// Detect method which is called in while read frame loop... public Mat detect(Mat inputframe){

        Imgproc.resize(webcam_image, resizeImage, new Size(320, 240));
        Mat mRgba=new Mat();
        inputframe.copyTo(mRgba); // The frame read from video source (camera, *.mp4, *.avi file etc)
        blurred = new Mat();
        fg = blurred.clone();
        thresholded = fg.clone();
        blob = thresholded.clone();
        gray = blob.clone();

        Imgproc.cvtColor(mRgba,gray,Imgproc.COLOR_BGR2GRAY);  // Before processing we convert to gray
        Imgproc.GaussianBlur(gray,blurred,new Size(3,3),0,0,Imgproc.BORDER_DEFAULT); // Avoid from unnecessary pixels

             bgs.apply(blurred,fg); // Extract background from scene                             

            Imgproc.threshold(fg,thresholded,70.0f,255,Imgproc.THRESH_BINARY); // Apply max and min threshold

        Mat elementCLOSE = new Mat(5,5,CvType.CV_8U,new Scalar(255,255,255));
        Imgproc.morphologyEx(thresholded,thresholded,Imgproc.MORPH_CLOSE,elementCLOSE); // Do a body figure analysis (for object scene change optimization)

        Mat v = new Mat();
        Imgproc.findContours(thresholded,contours,v, Imgproc.RETR_EXTERNAL,Imgproc.CHAIN_APPROX_SIMPLE); // Find the changes of scene (the moving parts)

        Imgproc.equalizeHist(gray, gray); // Balance the contrast to gain proper result

        int cmin = 500; 
        int cmax = 80000;
        MatOfRect rects = new MatOfRect();
        if (contours != null && !contours.isEmpty()) {
            //if (contours.size() >= 50) { // You may use this control and a threshold value if too much contour you have
                //Imgproc.drawContours(mRgba,contours,-1,new Scalar(0, 0, 255),2); // If you want you ...