private void Track()
{
if (image == null)
{
return;
}
// calculate the back projection of the current image on top of the initial histogram.
using (CVImage bp = image.CalcBackProject(this.initialHistogram))
{
// show the back projection.
backProjectImage.Image = bp.ToBitmap();
// calculate mean shift with user parameters and region of interest.
CVConnectedComp conn = bp.MeanShift(originalImage.SelectionRect, Iterations);
// update region of interest according to mean shift result.
originalImage.SelectionRect = conn.Rect;
}
// rotate update counter only if rate != 0.
if (UpdateHistogramRate != 0)
{
updateHistoCounter = (updateHistoCounter + 1) % UpdateHistogramRate;
// update histogram is counter reached 0.
if (updateHistoCounter == 0)
{
UpdateHistogram();
}
}
// refresh images.
RefreshImages();
}
private void ProcessMeanShift()
{
if (selectionHistogram == null)
{
return;
}
using (CVImage lastFrameClone = videoPlayer.LastFrame.Clone())
{
using (CVImage bp = videoPlayer.LastFrame.CalcBackProject(selectionHistogram))
{
CVConnectedComp cc = bp.MeanShift(video.SelectionRect, 100);
video.SelectionRect = cc.Rect;
}
}
}
private void ProcessRegionGrowing()
{
if (selectionHistogram == null)
{
return;
}
using (CVImage lastFrameClone = videoPlayer.LastFrame.Clone())
{
using (CVImage bp = videoPlayer.LastFrame.CalcBackProject(selectionHistogram))
{
CVConnectedComp cc = bp.MeanShift(video.SelectionRect, 100);
video.SelectionRect = cc.Rect;
Point midPoint = new Point(
video.SelectionRect.Left + video.SelectionRect.Width / 2,
video.SelectionRect.Top + video.SelectionRect.Height / 2);
using (CVImage rg = videoPlayer.Capture.CreateCompatibleImage())
{
rg.Zero();
OpenCVDotNet.Algorithms.RegionGrowing.Fill(midPoint, rg, new OpenCVDotNet.Algorithms.RegionGrowingCriteria(MyRGCriteria), videoPlayer.LastFrame);
growingFrame.Image = rg.ToBitmap();
if (overlay.Checked)
{
// go over regions in rg and overlay on output image.
for (int row = 0; row < rg.Height; row++)
{
for (int col = 0; col < rg.Width; ++col)
{
if (rg[row, col].GrayLevel != 0)
{
videoPlayer.LastFrame[row, col] = new CVRgbPixel(0, 100, 0);
}
}
}
}
video.Image = videoPlayer.LastFrame.ToBitmap();
}
}
}
}
private void NextFrame(bool track)
{
meanShiftNoMask.Image = videoPlayer.LastFrame.ToBitmap();
if (!track)
{
vot.Reset();
}
if (hist == null)
{
return;
}
using (CVImage backProj = videoPlayer.LastFrame.CalcBackProject(hist))
{
CVConnectedComp cc = backProj.MeanShift(meanShift.SelectionRect, 1);
vot.AddValue(cc.Area, Color.Blue);
if (cc.Area > MIN_AREA && cc.Area < MAX_AREA)
{
if (track)
{
meanShift.SelectionRect = cc.Rect;
}
}
bpWithMask.Image = backProj.ToBitmap();
}
OpenCVDotNet.UI.Statistics blueStats = vot.GetStatistics(Color.Blue);
if (blueStats != null)
{
avgWithMask.Text = ((int)blueStats.Average).ToString();
lastWithMask.Text = ((int)blueStats.LastValue).ToString();
}
if (histNoMask == null)
{
return;
}
using (CVImage backProjNoMask = videoPlayer.LastFrame.CalcBackProject(histNoMask))
{
CVConnectedComp cc = backProjNoMask.MeanShift(meanShiftNoMask.SelectionRect, 1);
vot.AddValue(cc.Area, Color.Red);
if (cc.Area > MIN_AREA && cc.Area < MAX_AREA)
{
if (track)
{
meanShiftNoMask.SelectionRect = cc.Rect;
}
}
bpNoMask.Image = backProjNoMask.ToBitmap();
}
OpenCVDotNet.UI.Statistics redStats = vot.GetStatistics(Color.Red);
if (redStats != null)
{
avgNoMask.Text = ((int)redStats.Average).ToString();
lastNoMask.Text = ((int)redStats.LastValue).ToString();
}
}
