基于训练卷积神经网络的人脸识别设计.zip

基于训练卷积神经网络alexnet的人脸识别设计，并采用级联目标检测技术对裁剪人脸进行识别。使用函数capturefacesfromvideo.m从视频获取训练数据，并存储人脸图像。使用函数cropface.m从训练数据的图像中裁剪人脸。通过改变各层的数量来训练卷积神经网络alexnet。使用训练后的newnet实现人脸识别。

% Create the face detector object.
faceDetector = vision.CascadeobjectDetector（‘FrontalFaceCART‘‘MinSize‘[150150]）;

% Here the loop runs for 300 times you can change the threshold （n） based on the number of training data you need
n = 300;

% change str to s01s02s03.... for saving  upto how many subjects you want to save for saving in respective folders for 
% imwrite in line 88

str = ‘s01‘;

% Create the point tracker object.
pointTracker = vision.PointTracker（‘MaxBidirectionalError‘ 2）;

% Create the webcam object.
cam = webcam（）;

% Capture one frame to get its size.
videoframe = snapshot（cam）;
frameSize = size（videoframe）;

% Create the video player object.
videoPlayer = vision.VideoPlayer（‘Position‘ [100 100 [frameSize（2） frameSize（1）]+30]）;
runLoop = true;
numPts = 0;
frameCount = 0;
i=1;

while runLoop && frameCount < n

    % Get the next frame.
    videoframe = snapshot（cam）;
    videoframeGray = rgb2gray（videoframe）;
    frameCount = frameCount + 1;

    if numPts < 10
        % Detection mode.
        bbox = faceDetector.step（videoframeGray）;

        if ~isempty（bbox）
            % Find corner points inside the detected region.
            points = detectMinEigenFeatures（videoframeGray ‘ROI‘ bbox（1 :））;

            % Re-initialize the point tracker.
            xyPoints = points.Location;
            numPts = size（xyPoints1）;
            release（pointTracker）;
            initialize（pointTracker xyPoints videoframeGray）;

            % Save a copy of the points.
            oldPoints = xyPoints;

            % Convert the rectangle represented as [x y w h] into an
            % M-by-2 matrix of [xy] coordinates of the four corners. This
            % is needed to be able to transform the bounding box to display
            % the orientation of the face.
            bboxPoints = bbox2points（bbox（1 :））;

            % Convert the box corners into the [x1 y1 x2 y2 x3 y3 x4 y4]
            % format required by insertShape.
            bboxPolygon = reshape（bboxPoints‘ 1 []）;

            % Display a bounding box around the detected face.
            videoframe = insertShape（videoframe ‘Polygon‘ bboxPolygon ‘LineWidth‘ 3）;

            % Display detected corners.
            videoframe = insertMarker（videoframe xyPoints ‘+‘ ‘Color‘ ‘white‘）;
        end

    else
        % Tracking mode.
        [xyPoints isFound] = step（pointTracker videoframeGray）;
        visiblePoints = xyPoints（isFound :）;
        oldInliers = oldPoints（isFound :）;

        numPts = size（visiblePoints 1）;

        if numPts >= 10
            % Estimate the geometric transformation between the old points
            % and the new points.
            [xform oldInliers visiblePoints] = estimateGeometricTransform（...
                oldInliers visiblePoints ‘similarity‘ ‘MaxDistance‘ 4）;

            % Apply the transformation to the bounding box.
            bboxPoints = transformPointsForward（xform bboxPoints）;

            % 

 属性            大小     日期    时间   名称
----------- ---------  ---------- -----  ----
     目录           0  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\
     文件         538  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\README.md
     文件        1696  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\SimpleFaceRecognition.m
     目录           0  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\Training Progress Report\
     文件      136452  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\Training Progress Report\Training Progress Plot.JPG
     文件         212  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\Training Progress Report\Training Progress Report.txt
     文件        3993  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\capturefacesfromvideo.m
     文件         276  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\cropandsave.m
     文件         276  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\cropface.m
     目录           0  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\croppedfaces\
     文件         181  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\croppedfaces\readme.txt
     目录           0  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\croppedfaces\s01\
     文件         181  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\croppedfaces\s01\readme.txt
     目录           0  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\croppedfaces\s02\
     文件         181  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\croppedfaces\s02\readme.txt
     目录           0  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\croppedfaces\s03\
     文件         181  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\croppedfaces\s03\readme.txt
     目录           0  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\photos\
     文件         165  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\photos\readme.txt
     目录           0  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\photos\s01\
     文件         165  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\photos\s01\readme.txt
     目录           0  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\photos\s02\
     文件         165  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\photos\s02\readme.txt
     目录           0  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\photos\s03\
     文件         165  2019-07-09 08:20  Yash0330-Face-Recognition-by-CNN-464efe8\photos\s03\readme.txt