Detecting face very fast from video using vision.Cas​cadeObject​Detector in matlab code

I wrote matlab code for face detection.In my code it is detecting face for first 100 frames and it crop faces from each frame and saves it in database folder.Problems iam facing

1.Detecting frame by frame is very slow.Is there any idea to run faster since i have to work on 4000 frames.

2.In my database folder it has to show 1 to 100 face images but it is not showing 11th and 12th face images directly it showing 13th face image after 10th image.23rd face image is blurr.Likewise so many images are missing and some are blurr.Last image number it is showing as 216.But total 106 face images are there.12 images are blurr.

      clc;
      clear all;

      obj=vision.VideoFileReader('basu.avi');

      for k=0:99

      videoFrame      = step(obj);

            FaceDetect = vision.CascadeObjectDetector;

           %FaceDetect
            BB = step(FaceDetect,videoFrame);
            %BB
             figure(2),imshow(videoFrame);

      for i = 1:size(BB,1)
            rectangle('Position',BB(i,:),'LineWidth',3,'LineStyle','-','EdgeColor','r');
      end

      %crop faces and convert it to gray
      for i = 1:size(BB,1)
      J= imcrop(videoFrame,BB(i,:));
      I=rgb2gray(imresize(J,[292,376]));

      %save cropped faces in folder
      filename = ['G:\matlab_installed\bin\database\' num2str(i+k*(size(BB,1))) '.jpg'];
          imwrite(I,filename);
      end
      end

[prashanth]

No One is there to answer my question?

[prashanth]

Elapsed time is 130.401650 seconds.I used tic()and toc() for whole code

[Aishwarya Hunashal]

By using above code i am getting cropped frames without faces also how to solve this?please help me

Answer 1

[Dima Lisin]

There are a few of things you can try:

Definitely move FaceDetect = vision.CascadeObjectDetector; outside of the loop. You only need to create the face detector object once. Re-creating it for every frame is definitely your performance bottleneck.

vision.VideoFileReader returns a frame of class 'single' by default. If you change the output data type to 'uint8', that should speed up the face detector. Use obj=vision.VideoFileReader('basu.avi', 'VideoOutputDataType', 'uint8');

vision.VideoFileReader can also do the conversion to grayscale for you. Use obj=vision.VideoFileReader('basu.avi', 'VideoOutputDataType', 'uint8', 'ImageColorSpace', 'Intensity'); This may be faster than calling rgb2gray.

Try limiting the size of the faces being detected using 'MinSize' and 'MaxSize' options of vision.CascadeObjectDetector and/or try downsampling the frame before detecting faces.