使用MATLAB机器视觉工具箱实现人脸的检测和跟踪

跟图像处理、机器人视觉相关的MATLAB工具箱有：

Image Processing Toolbox （图像处理工具箱）

Computer Vision System Toolbox （计算机视觉工具箱）

Image Acquisition Toolbox （图像采集工具箱）

一般情况下，一个完整的机器人视觉应用需要用到这三个工具箱（我会近期开发一个使用MATLAB实现的家庭安全检测系统，可以详细讲解一下整个流程）

第一步：检测人脸

<span style="font-size:14px;">% 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.
boxInserter  = vision.ShapeInserter('BorderColor','Custom',...
    'CustomBorderColor',[255 255 0]);
videoOut = step(boxInserter, videoFrame,bbox);
figure, imshow(videoOut), title('Detected face');</span>

实际引用中，大家可以把读取的avi文件，换成摄像机实时数据的获取。

第二步：从检测到的人脸里提取重要的特征，用于第三步的人脸追踪使用

<span style="font-size:14px;">% 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])</span>

这里面，我们把rgb图像转换成HSV图像

第三步：人脸追踪

<span style="font-size:14px;">% 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);
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(1:2) = noseBBox(1:2) + bbox(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);

% 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 = step(boxInserter, videoFrame, bbox);

    % Display the annotated video frame using the video player object
    step(videoPlayer, videoOut);

end

% Release resources
release(videoFileReader);
release(videoPlayer);</span>

怎样将测试视频换成从摄像头读入，解释如下，具体可看原文评论：点击打开链接

你要是有新版matlab (好像2014b之后)，可以用webcam function

http://www.mathworks.com/help/su ... cams/ug/webcam.html

或者看image acquisition toolbox里面的example

http://www.mathworks.com/products/imaq/code-examples.html