private void processImage(Image<Bgr, byte> frame, out Image<Gray, byte> probabilityMap, out Rectangle prevSearchArea, out Box2D foundBox)
{
prevSearchArea = searchArea;
//convert to HSV
var hsvImg = frame.Convert<Hsv, byte>(); //<<parallel operation>>
//back-project ratio hist => create probability map
probabilityMap = ratioHist.BackProject(hsvImg.SplitChannels(0, 1)); //or new Image<Gray, byte>[]{ hsvImg[0], hsvImg[1]...} //<<parallel operation>>
//user constraints...
Image<Gray, byte> mask = hsvImg.InRange(new Hsv(0, 0, minV), new Hsv(0, 0, maxV), Byte.MaxValue, 2);
probabilityMap.And(mask, inPlace:true);
//run Camshift algorithm to find new object position, size and angle
foundBox = Camshift.Process(probabilityMap, searchArea); //<<parallel operation>>
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 trackCamshift(Image<Bgr, byte> frame, Rectangle searchArea, out Image<Gray, byte> probabilityMap, out Box2D foundBox)
{
const int PROBABILITY_MIN_VAL = (int)(0.3f * Byte.MaxValue);
//convert to HSV
var hsvImg = frame.Convert<Hsv, byte>(); //<<parallel operation>>
//back-project ratio hist => create probability map
probabilityMap = ratioHist.BackProject(hsvImg.SplitChannels(0, 1)); //or new Image<Gray, byte>[]{ hsvImg[0], hsvImg[1]...} //<<parallel operation>>
//user constraints...
Image<Gray, byte> mask = hsvImg.InRange(new Hsv(0, 0, minV), new Hsv(0, 0, maxV), Byte.MaxValue, 2);
probabilityMap.And(mask, inPlace: true);
//run Camshift algorithm to find new object position, size and angle
CentralMoments centralMoments;
foundBox = Camshift.Process(probabilityMap, searchArea, Meanshift.DEFAULT_TERM, out centralMoments); //<<parallel operation>>
//stopping conditions
float avgIntensity = centralMoments.Mu00 / (foundBox.Size.Area() + Single.Epsilon);
if (avgIntensity < PROBABILITY_MIN_VAL || foundBox.Size.IsEmpty || foundBox.GetMinArea().Area() < 5 * 5)
{
foundBox = Box2D.Empty; //invalid box
}
}
private void trackOneStep(Image<Bgr, byte> frame, out Image<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 > 80) //if not visible for a longer time => reset tracking
{
nonVisibleCount = 0;
isROISelected = false;
}
}
