How to make matching for face recognition

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close all
clear
clc
%%Load Video Process
faceDetector = vision.CascadeObjectDetector();
% Read a video frame and run the detector.
videoFileReader = vision.VideoFileReader('shahmeer_1.mp4');
videoFrame      = step(videoFileReader);
bbox            = step(faceDetector, videoFrame);
% Draw the returned bounding box around the detected face.
videoOut = insertObjectAnnotation(videoFrame,'rectangle',bbox,'Face');
% figure, imshow(videoOut), title('Detected face');
% Convert the first box into a list of 4 points
% This is needed to be able to visualize the rotation of the object.
bboxPoints = bbox2points(bbox(1, :));
%%Face Region Process
points = detectMinEigenFeatures(rgb2gray(videoFrame), 'ROI', bbox);
% Display the detected points.
% figure, imshow(videoFrame), hold on, title('Detected features');
% plot(points);
%%KLT Process
pointTracker = vision.PointTracker('MaxBidirectionalError', 2);
% Initialize the tracker with the initial point locations and the initial
% video frame.
points = points.Location;
initialize(pointTracker, points, videoFrame);
videoPlayer  = vision.VideoPlayer('Position',...
    [100 100 [size(videoFrame, 2), size(videoFrame, 1)]+30]);
oldPoints = points;
while ~isDone(videoFileReader)
    % get the next frame
    videoFrame = step(videoFileReader);
      % Track the points. Note that some points may be lost.
      [points, isFound] = step(pointTracker, videoFrame);
      visiblePoints = points(isFound, :);
      oldInliers = oldPoints(isFound, :);
      if size(visiblePoints, 1) >= 2 % need at least 2 points
          % Estimate the geometric transformation between the old points
          % and the new points and eliminate outliers
          [xform, oldInliers, visiblePoints] = estimateGeometricTransform(...
              oldInliers, visiblePoints, 'similarity', 'MaxDistance', 4);
          % Apply the transformation to the bounding box points
          bboxPoints = transformPointsForward(xform, bboxPoints);
          % Insert a bounding box around the object being tracked
          bboxPolygon = reshape(bboxPoints', 1, []);
          videoFrame = insertShape(videoFrame, 'Polygon', bboxPolygon, ...
              'LineWidth', 2);
          % Display tracked points
          videoFrame = insertMarker(videoFrame, visiblePoints, '+', ...
              'Color', 'white');
          % Reset the points
          oldPoints = visiblePoints;
          setPoints(pointTracker, oldPoints);
      end
      % Display the annotated video frame using the video player object
      step(videoPlayer, videoFrame);
  end
% Clean up
release(videoFileReader);
release(videoPlayer);
release(pointTracker);
[idx,C] = kmeans(points,1);