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 }