HELP, How to do real time face tracking in matlab?

3 vues (au cours des 30 derniers jours)
Anand le 20 Fév 2014
Commenté : VALARMATHY K le 21 Août 2017
Hi, can someone PLEASE tell me how to track a face in a real time video using A webcam in MATLAB. Im using this sample code which outputs a video file with my face being being tracked. All i want it to do is to track my face live using the webcam. Its probably a small change in the code but i have no idea how to do it.
Can anybody please help me with this?
Detect the face
% Create a cascade detector object.
faceDetector = vision.CascadeObjectDetector();
% Read a video frame and run the detector.
videoFileReader = vision.VideoFileReader('facevid.WMV');
videoFrame = step(videoFileReader);
bbox = step(faceDetector, videoFrame);
% Draw the returned bounding box around the detected face.
videoOut = insertObjectAnnotation(videoFrame,'rectangle',bbox,'Face');
figure, imshow(videoOut), title('Detected face');
% Get the skin tone information by extracting the Hue from the video frame
% converted to the HSV color space.
[hueChannel,~,~] = rgb2hsv(videoFrame);
% Display the Hue Channel data and draw the bounding box around the face.
figure, imshow(hueChannel), title('Hue channel data');
rectangle('Position',bbox(1,:),'LineWidth',2,'EdgeColor',[1 1 0])
Track the face
% Detect the nose within the face region. The nose provides a more accurate
% measure of the skin tone because it does not contain any background
% pixels.
noseDetector = vision.CascadeObjectDetector('Nose');
faceImage = imcrop(videoFrame,bbox(1,:));
noseBBox = step(noseDetector,faceImage);
% The nose bounding box is defined relative to the cropped face image.
% Adjust the nose bounding box so that it is relative to the original video
% frame.
noseBBox(1,1:2) = noseBBox(1,1:2) + bbox(1,1:2);
% Create a tracker object.
tracker = vision.HistogramBasedTracker;
% Initialize the tracker histogram using the Hue channel pixels from the
% nose.
initializeObject(tracker, hueChannel, noseBBox(1,:));
% Create a video player object for displaying video frames.
videoInfo = info(videoFileReader);
videoPlayer = vision.VideoPlayer('Position',[300 300 videoInfo.VideoSize+30]);
% Track the face over successive video frames until the video is finished.
while ~isDone(videoFileReader)
% Extract the next video frame
videoFrame = step(videoFileReader);
% RGB -> HSV
[hueChannel,~,~] = rgb2hsv(videoFrame);
% Track using the Hue channel data
bbox = step(tracker, hueChannel);
% Insert a bounding box around the object being tracked
videoOut = insertObjectAnnotation(videoFrame,'rectangle',bbox,'Face');
% Display the annotated video frame using the video player object
step(videoPlayer, videoOut);
% Release resources

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Anand le 21 Fév 2014
You can use imaqhwinfo to see which cameras are connected to your machine and then accordingly use the videoinput command to connect to the camera of your choice. Within the loop, use the getsnapshot command to capture an image.
This video should be helpful:
  8 commentaires
Anand le 27 Fév 2014
i have managed to read the video frames, but how do i extract them in screen shots?
videoFReader = vision.VideoFileReader('face.avi');
videoPlayer = vision.VideoPlayer;
while ~isDone(videoFReader)
videoFrame = step(videoFReader);
step(videoPlayer, videoFrame);
VALARMATHY K le 21 Août 2017
you can use this code
obj = VideoReader('cute.mp4');
vid = read(obj); frames = obj.NumberOfFrames; ST='.jpg';
for x = 1:25

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