%%
clear all;
clc;
%%
convnet = alexnet;
featureLayer = 'fc7';
load('FACE_classifier');
% Create the face detector object.
faceDetector = vision.CascadeObjectDetector();
faceDetector.MergeThreshold=9;
% 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;
while runLoop
% 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(xyPoints,1);
pause(0.5); title('test Image');
test=imcrop(videoFrame,bbox);
imshow(test);
testSet = imresize(test, [227 227]);
testFeatures = activations(convnet, testSet, featureLayer);
predictedLabels = predict(FACE_classifier, testFeatures)
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 [x,y] 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);
% 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 face being tracked.
videoFrame = insertShape(videoFrame, 'Polygon', bboxPolygon, 'LineWidth', 3);
% Display tracked points.
videoFrame = insertMarker(videoFrame, visiblePoints, '+', 'Color', 'white');
% Reset the points.
oldPoints = visiblePoints;
setPoints(pointTracker, oldPoints);
end
end
% Display the annotated video frame using the video player object.
step(videoPlayer, videoFrame);
% Check whether the video player window has been closed.
runLoop = isOpen(videoPlayer);
end
% Clean up. clear cam; release(videoPlayer); release(pointTracker); release(faceDetector);