我正在尝试使用 MATLAB 制作实时人脸检测器。我在 Mathworks 的页面上找到了示例代码，但它使用了示例视频。我遇到的问题是，即使在开始框架中有几张面孔，此代码也只能跟踪它选择的那个。我需要它一次跟踪多个面孔。是否可以通过不剧烈的更改此代码来实现。我在 MathWorks 的网页上找到了以下代码：
% Create a cascade detector object.
faceDetector = vision.CascadeObjectDetector();
% Read a video frame and run the detector.
videoFileReader = vision.VideoFileReader('visionface.avi');
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])
% 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);
end
% Release resources
release(videoFileReader);
release(videoPlayer);
提前致谢！