private void ComputeSparseOpticalFlow()
{
// Compute optical flow using pyramidal Lukas Kanade Method
OpticalFlow.PyrLK(grayFrame, nextGrayFrame, ActualFeature[0], new System.Drawing.Size(10, 10), 3, new MCvTermCriteria(20, 0.03d), out NextFeature, out Status, out TrackError);
using (MemStorage storage = new MemStorage())
nextHull = PointCollection.ConvexHull(ActualFeature[0], storage, Emgu.CV.CvEnum.ORIENTATION.CV_CLOCKWISE).ToArray();
nextCentroid = FindCentroid(nextHull);
for (int i = 0; i < ActualFeature[0].Length; i++)
{
DrawTrackedFeatures(i);
//Uncomment this to draw optical flow vectors
DrawFlowVectors(i);
}
}
private void InitializeFaceTracking()
{
_faces = new HaarCascade("haarcascade_frontalface_alt_tree.xml");
frame = _capture.QueryFrame();
//We convert it to grayscale
grayFrame = frame.Convert <Gray, Byte>();
// We detect a face using haar cascade classifiers, we'll work only on face area
faceDetected = grayFrame.DetectHaarCascade(_faces, 1.1, 1, Emgu.CV.CvEnum.HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(20, 20));
if (faceDetected[0].Length == 1)
{
trackingArea = new Rectangle(faceDetected[0][0].rect.X, faceDetected[0][0].rect.Y, faceDetected[0][0].rect.Width, faceDetected[0][0].rect.Height);
// Here we enlarge or restrict the search features area on a smaller or larger face area
float scalingAreaFactor = 0.6f;
int trackingAreaWidth = (int)(faceDetected[0][0].rect.Width * scalingAreaFactor);
int trackingAreaHeight = (int)(faceDetected[0][0].rect.Height * scalingAreaFactor);
int leftXTrackingCoord = faceDetected[0][0].rect.X - (int)(((faceDetected[0][0].rect.X + trackingAreaWidth) - (faceDetected[0][0].rect.X + faceDetected[0][0].rect.Width)) / 2);
int leftYTrackingCoord = faceDetected[0][0].rect.Y - (int)(((faceDetected[0][0].rect.Y + trackingAreaHeight) - (faceDetected[0][0].rect.Y + faceDetected[0][0].rect.Height)) / 2);
trackingArea = new Rectangle(leftXTrackingCoord, leftYTrackingCoord, trackingAreaWidth, trackingAreaHeight);
// Allocating proper working images
faceImage = new Image <Bgr, Byte>(trackingArea.Width, trackingArea.Height);
faceGrayImage = new Image <Gray, Byte>(trackingArea.Width, trackingArea.Height);
frame.ROI = trackingArea;
frame.Copy(faceImage, null);
frame.ROI = Rectangle.Empty;
faceGrayImage = faceImage.Convert <Gray, Byte>();
// Detecting good features that will be tracked in following frames
ActualFeature = faceGrayImage.GoodFeaturesToTrack(400, 0.5d, 5d, 5);
faceGrayImage.FindCornerSubPix(ActualFeature, new Size(5, 5), new Size(-1, -1), new MCvTermCriteria(25, 1.5d));
// Features computed on a different coordinate system are shifted to their original location
for (int i = 0; i < ActualFeature[0].Length; i++)
{
ActualFeature[0][i].X += trackingArea.X;
ActualFeature[0][i].Y += trackingArea.Y;
}
// Computing convex hull
using (MemStorage storage = new MemStorage())
hull = PointCollection.ConvexHull(ActualFeature[0], storage, Emgu.CV.CvEnum.ORIENTATION.CV_CLOCKWISE).ToArray();
referenceCentroid = FindCentroid(hull);
}
}
//Code adapted and improved from: http://blog.csharphelper.com/2010/01/04/find-a-polygons-centroid-in-c.aspx
// refer to wikipedia for math formulas centroid of polygon http://en.wikipedia.org/wiki/Centroid
private PointF FindCentroid(PointF[] Feature)
{
PointF[] Hull;
// Computing convex hull
using (MemStorage storage = new MemStorage())
Hull = PointCollection.ConvexHull(Feature, storage, Emgu.CV.CvEnum.ORIENTATION.CV_CLOCKWISE).ToArray();
// Add the first point at the end of the array.
int num_points = Hull.Length;
PointF[] pts = new PointF[num_points + 1];
Hull.CopyTo(pts, 0);
pts[num_points] = Hull[0];
// Find the centroid.
float X = 0;
float Y = 0;
float second_factor;
for (int i = 0; i < num_points; i++)
{
second_factor = pts[i].X * pts[i + 1].Y - pts[i + 1].X * pts[i].Y;
X += (pts[i].X + pts[i + 1].X) * second_factor;
Y += (pts[i].Y + pts[i + 1].Y) * second_factor;
}
// Divide by 6 times the polygon's area.
float polygon_area = Math.Abs(SignedPolygonArea(Hull));
X /= (6 * polygon_area);
Y /= (6 * polygon_area);
// If the values are negative, the polygon is
// oriented counterclockwise so reverse the signs.
if (X < 0)
{
X = -X;
Y = -Y;
}
return(new PointF(X, Y));
}