多张面孔检测与跟踪
内容
-
环境配置
-
运行代码
1.1 访问:Webcam Support Package。击右下角位置的download,下载Webcam安装包
1.2 需要将安装包放在matlab 的当前路径,双击 usbwebcams.mlpkginstall
1.3 点击该文件根据提示,进行安装
在安装完成结束后,在命令行输入:webcam后出现下图属性情况,则说明安装成功
运行代码
%% detectAndTrackFaces
% Automatically detects and tracks multiple faces in a webcam-acquired
% video stream.
%
% Copyright 2013-2014 The MathWorks, Inc
clear classes;
%% Instantiate video device, face detector, and KLT object tracker
vidObj = webcam;
faceDetector = vision.CascadeObjectDetector(); % Finds faces by default
tracker = MultiObjectTrackerKLT;
%% Get a frame for frame-size information
frame = snapshot(vidObj);
frameSize = size(frame);
%% Create a video player instance
videoPlayer = vision.VideoPlayer('Position',[200 100 fliplr(frameSize(1:2)+30)]);
%% Iterate until we have successfully detected a face
bboxes = [];
while isempty(bboxes)
framergb = snapshot(vidObj);
frame = rgb2gray(framergb);
bboxes = faceDetector.step(frame);
end
tracker.addDetections(frame, bboxes);
%% And loop until the player is closed
frameNumber = 0;
keepRunning = true;
disp('Press Ctrl-C to exit...');
while keepRunning
framergb = snapshot(vidObj);
frame = rgb2gray(framergb);
if mod(frameNumber, 10) == 0
% (Re)detect faces.
%
% NOTE: face detection is more expensive than imresize; we can
% speed up the implementation by reacquiring faces using a
% downsampled frame:
% bboxes = faceDetector.step(frame);
bboxes = 2 * faceDetector.step(imresize(frame, 0.5));
if ~isempty(bboxes)
tracker.addDetections(frame, bboxes);
end
else
% Track faces
tracker.track(frame);
end
% Display bounding boxes and tracked points.
displayFrame = insertObjectAnnotation(framergb, 'rectangle',...
tracker.Bboxes, tracker.BoxIds);
displayFrame = insertMarker(displayFrame, tracker.Points);
videoPlayer.step(displayFrame);
frameNumber = frameNumber + 1;
end
%% Clean up
release(videoPlayer);
运行效果图(因为是夜晚,只有我一人检测,所有没有多目标检测)
今天又测试一下,把我妈喊过来测试一下,感觉还不错,2020-1-14完!