private void initTracking(Bgr<byte>[,] frame)
{
//get hue channel from search area
var hsvImg = frame.ToHsv();
//user constraints...
Gray<byte>[,] mask = hsvImg.InRange(new Hsv<byte>(0, 0, (byte)minV), new Hsv<byte>(0, 0, (byte)maxV), Byte.MaxValue, 2);
originalObjHist.Calculate(hsvImg.SplitChannels<Hsv<byte>, byte>(roi, 0, 1), !false, mask, roi.Location);
originalObjHist.Scale((float)1 / roi.Area());
//originalObjHist.Normalize(Byte.MaxValue);
var backgroundArea = roi.Inflate(1.5, 1.5, frame.Size());
backgroundHist.Calculate(hsvImg.SplitChannels<Hsv<byte>, byte>(backgroundArea, 0, 1), !false, mask, backgroundArea.Location);
backgroundHist.Scale((float)1 / backgroundArea.Area());
//backgroundHist.Normalize(Byte.MaxValue);
//how good originalObjHist and objHist match (suppresses possible selected background)
ratioHist = originalObjHist.CreateRatioHistogram(backgroundHist, Byte.MaxValue, 10);
searchArea = roi;
roi = Rectangle.Empty;
}
private void processImage(Bgr <byte>[,] frame, out Gray <byte>[,] probabilityMap, out Rectangle prevSearchArea, out Box2D foundBox)
{
prevSearchArea = searchArea;
//convert to HSV
var hsvImg = frame.ToHsv();
//back-project ratio hist => create probability map
probabilityMap = ratioHist.BackProject(hsvImg.SplitChannels <Hsv <byte>, byte>(0, 1)); //or new Image<Gray<byte>>[]{ hsvImg[0], hsvImg[1]...}
//user constraints...
Gray <byte>[,] mask = hsvImg.InRange(new Hsv <byte>(0, 0, (byte)minV), new Hsv <byte>(0, 0, (byte)maxV), Byte.MaxValue, 2);
probabilityMap.AndByte(mask, inPlace: true);
//run Camshift algorithm to find new object position, size and angle
foundBox = Camshift.Process(probabilityMap, searchArea);
var foundArea = Rectangle.Round(foundBox.GetMinArea());
searchArea = foundArea.Inflate(0.05, 0.05, frame.Size()); //inflate found area for search (X factor)...
if (searchArea.IsEmpty)
{
isROISelected = false; //reset tracking
}
}
private void initTracking(Bgr <byte>[,] frame)
{
//get hue channel from search area
var hsvImg = frame.ToHsv();
//user constraints...
Gray <byte>[,] mask = hsvImg.InRange(new Hsv <byte>(0, 0, (byte)minV), new Hsv <byte>(0, 0, (byte)maxV), Byte.MaxValue, 2);
originalObjHist.Calculate(hsvImg.SplitChannels <Hsv <byte>, byte>(roi, 0, 1), !false, mask, roi.Location);
originalObjHist.Scale((float)1 / roi.Area());
//originalObjHist.Normalize(Byte.MaxValue);
var backgroundArea = roi.Inflate(1.5, 1.5, frame.Size());
backgroundHist.Calculate(hsvImg.SplitChannels <Hsv <byte>, byte>(backgroundArea, 0, 1), !false, mask, backgroundArea.Location);
backgroundHist.Scale((float)1 / backgroundArea.Area());
//backgroundHist.Normalize(Byte.MaxValue);
//how good originalObjHist and objHist match (suppresses possible selected background)
ratioHist = originalObjHist.CreateRatioHistogram(backgroundHist, Byte.MaxValue, 10);
searchArea = roi;
roi = Rectangle.Empty;
}
private void trackOneStep(Bgr<byte>[,] frame, out Gray<byte>[,] probabilityMap, out Box2D foundBox)
{
const float SEARCH_AREA_INFLATE_FACTOR = 0.05f;
/**************************** KALMAN predict **************************/
kalman.Predict();
searchArea = createRect(kalman.State.Position, searchArea.Size, frame.Size());
/**************************** KALMAN predict **************************/
trackCamshift(frame, searchArea, out probabilityMap, out foundBox);
if (!foundBox.IsEmpty)
{
/**************************** KALMAN correct **************************/
kalman.Correct(new PointF(foundBox.Center.X, foundBox.Center.Y)); //correct predicted state by measurement
/**************************** KALMAN correct **************************/
var foundArea = Rectangle.Round(foundBox.GetMinArea());
searchArea = foundArea.Inflate(SEARCH_AREA_INFLATE_FACTOR, SEARCH_AREA_INFLATE_FACTOR, frame.Size()); //inflate found area for search (X factor)...
nonVisibleCount = 0;
}
else
{
nonVisibleCount++;
if (nonVisibleCount == 1) //for the first time
{
searchArea = searchArea.Inflate(-SEARCH_AREA_INFLATE_FACTOR * 1.5, -SEARCH_AREA_INFLATE_FACTOR * 1.5, frame.Size()); //shrink (hysteresis)
}
searchArea = createRect(kalman.State.Position, searchArea.Size, frame.Size());
}
if (nonVisibleCount > 100) //if not visible for a longer time => reset tracking
{
nonVisibleCount = 0;
isROISelected = false;
}
}
private void pictureBox_MouseUp(object sender, MouseEventArgs e)
{
roi.Intersect(new Rectangle(new Point(), frame.Size()));
isROISelected = true;
}
private void processImage(Bgr<byte>[,] frame, out Gray<byte>[,] probabilityMap, out Rectangle prevSearchArea, out Box2D foundBox)
{
prevSearchArea = searchArea;
//convert to HSV
var hsvImg = frame.ToHsv();
//back-project ratio hist => create probability map
probabilityMap = ratioHist.BackProject(hsvImg.SplitChannels<Hsv<byte>, byte>(0, 1)); //or new Image<Gray<byte>>[]{ hsvImg[0], hsvImg[1]...}
//user constraints...
Gray<byte>[,] mask = hsvImg.InRange(new Hsv<byte>(0, 0, (byte)minV), new Hsv<byte>(0, 0, (byte)maxV), Byte.MaxValue, 2);
probabilityMap.AndByte(mask, inPlace:true);
//run Camshift algorithm to find new object position, size and angle
foundBox = Camshift.Process(probabilityMap, searchArea);
var foundArea = Rectangle.Round(foundBox.GetMinArea());
searchArea = foundArea.Inflate(0.05, 0.05, frame.Size()); //inflate found area for search (X factor)...
if (searchArea.IsEmpty) isROISelected = false; //reset tracking
}