matlab调用摄像头人脸识别,matlab-调用摄像头人脸识别
标签：
----------------------------边学边写边学习-------------------------------------
版本：2014a
调用摄像头
a = imaqhwinfo
警告: No Image Acquisition adaptors found. Image acquisition adaptors may be available as downloadable support packages. Open Support Package Installer to install additional vendors.
这时候Support Package Installer在MATLAB里面有下划线，然后你点开它，MATLAB会提供大概13个软件包，这时候选择OS Generic Video Interface下载安装就OK了 (要求注册账号，随便用个邮箱注册下就可以了，不需要付费)。
下面就是调用笔记本电脑摄像头并打开图像
vidDevice = imaq.VideoDevice('winvideo', 1, 'YUY2_640x480', ...
'ROI', [1 1 640 480], ...
'ReturnedColorSpace', 'rgb' );
preview(vidDevice);
人脸检测我们用的是matlab的机器视觉工具箱(瞬间觉得matlab真心强大)
VJ算法的目的是检测人脸，但是其思想同样可以用于检测其他物体，只需进行训练即可。
VJ算法在Matlab里面实现的时候，已经训练好了正脸、侧脸、上半身、眼睛、嘴、鼻子，这些都是可以直接检测，不需训练，直接调用CascadeObjectDetector函数即可。
下面是检测人脸和上半身的例子
% Example 1: Face detection
% ----------------------------
faceDetector = vision.CascadeObjectDetector; % Default: finds faces
I = imread('visionteam.jpg');
bboxes = step(faceDetector, I); % Detect faces
% Annotate detected faces
IFaces = insertObjectAnnotation(I, 'rectangle', bboxes, 'Face');
figure, imshow(IFaces), title('Detected faces');
% Example 2: Upper body detection
% --------------------------------------
bodyDetector = vision.CascadeObjectDetector('UpperBody');
bodyDetector.MinSize = [60 60];
bodyDetector.MergeThreshold = 10;
I2 = imread('visionteam.jpg');
bboxBody = step(bodyDetector, I2); % Detect upper bodies
% Annotate detected upper bodies
IBody = insertObjectAnnotation(I2, 'rectangle', ...
bboxBody, 'Upper Body');
figure, imshow(IBody), title('Detected upper bodies');
至于调用摄像头进行人脸识别，肯定是 调用摄像头的过程中对每一帧图像分别进行识别，然后再在图像中框出来。
这就要求 速度 要足够快。所以检测的时候就要压缩你图像的像素了。
下面放代码
faceDetector = vision.CascadeObjectDetector(); %enable viola jones algorithm
bbox = [100 100 100 100];
vidDevice = imaq.VideoDevice('winvideo', 1, 'YUY2_640x480', ...
'ROI', [1 1 640 480], ...
'ReturnedColorSpace', 'rgb' );
%set(vidDevice.DeviceProperties, 'FrameRate', '30');
boxInserter = vision.ShapeInserter('BorderColor','Custom',...
'CustomBorderColor',[255 255 0]);
textInserter = vision.TextInserter('%d','LocationSource','Input port','Color',[255,255, 0],'FontSize',12);
nFrame =300;
vidInfo = imaqhwinfo(vidDevice);
vidHeight = vidInfo.MaxHeight;
vidWidth = vidInfo.MaxWidth;
videoPlayer = vision.VideoPlayer('Position',[300 100 640+30 480+30]);
for k = 1:nFrame % start recording with 300 frames
tic; % timer start
videoFrame = step(vidDevice); % enable the image capture by webcam
bbox = 4 * faceDetector.step(imresize(videoFrame, 1/4)); % boost video's fps
videoOut = step(boxInserter, videoFrame, bbox); % highlight the boxes of face at video
%release(boxInserter);
step(videoPlayer, videoOut); % display the video live in video player
end
一共执行了300帧，下面放图。
标签：
来源： https://www.cnblogs.com/hyb965149985/p/10193075.html