// Use the CamShift algorithm to track to base histogram throughout the
// succeeding frames
void CalculateCamShift(CvMat _image)
{
CvMat _backProject = CalculateBackProjection(_image, _histogramToTrack);
// Create convolution kernel for erosion and dilation
IplConvKernel elementErode = Cv.CreateStructuringElementEx(10, 10, 5, 5, ElementShape.Rect, null);
IplConvKernel elementDilate = Cv.CreateStructuringElementEx(4, 4, 2, 2, ElementShape.Rect, null);
// Try eroding and then dilating the back projection
// Hopefully this will get rid of the noise in favor of the blob objects.
Cv.Erode(_backProject, _backProject, elementErode, 1);
Cv.Dilate(_backProject, _backProject, elementDilate, 1);
if (backprojWindowFlag)
{
Cv.ShowImage("Back Projection", _backProject);
}
// Parameters returned by Camshift algorithm
CvBox2D _outBox;
CvConnectedComp _connectComp;
// Set the criteria for the CamShift algorithm
// Maximum 10 iterations and at least 1 pixel change in centroid
CvTermCriteria term_criteria = Cv.TermCriteria(CriteriaType.Iteration | CriteriaType.Epsilon, 10, 1);
// Draw object center based on Kalman filter prediction
CvMat _kalmanPrediction = _kalman.Predict();
int predictX = Mathf.FloorToInt((float)_kalmanPrediction.GetReal2D(0, 0));
int predictY = Mathf.FloorToInt((float)_kalmanPrediction.GetReal2D(1, 0));
// Run the CamShift algorithm
if (Cv.CamShift(_backProject, _rectToTrack, term_criteria, out _connectComp, out _outBox) > 0)
{
// Use the CamShift estimate of the object center to update the Kalman model
CvMat _kalmanMeasurement = Cv.CreateMat(2, 1, MatrixType.F32C1);
// Update Kalman model with raw data from Camshift estimate
_kalmanMeasurement.Set2D(0, 0, _outBox.Center.X); // Raw X position
_kalmanMeasurement.Set2D(1, 0, _outBox.Center.Y); // Raw Y position
//_kalmanMeasurement.Set2D (2, 0, _outBox.Center.X - lastPosition.X);
//_kalmanMeasurement.Set2D (3, 0, _outBox.Center.Y - lastPosition.Y);
lastPosition.X = Mathf.FloorToInt(_outBox.Center.X);
lastPosition.Y = Mathf.FloorToInt(_outBox.Center.Y);
_kalman.Correct(_kalmanMeasurement); // Correct Kalman model with raw data
// CamShift function returns two values: _connectComp and _outBox.
// _connectComp contains is the newly estimated position and size
// of the region of interest. This is passed into the subsequent
// call to CamShift
// Update the ROI rectangle with CamShift's new estimate of the ROI
_rectToTrack = CheckROIBounds(_connectComp.Rect);
// Draw a rectangle over the tracked ROI
// This method will draw the rectangle but won't rotate it.
_image.DrawRect(_rectToTrack, CvColor.Aqua);
_image.DrawMarker(predictX, predictY, CvColor.Aqua);
// _outBox contains a rotated rectangle esimating the position, size, and orientation
// of the object we want to track (specified by the initial region of interest).
// We then take this estimation and draw a rotated bounding box.
// This method will draw the rotated rectangle
rotatedBoxToTrack = _outBox;
// Draw a rotated rectangle representing Camshift's estimate of the
// object's position, size, and orientation.
_image.DrawPolyLine(rectangleBoxPoint(_outBox.BoxPoints()), true, CvColor.Red);
}
else
{
//Debug.Log ("Object lost by Camshift tracker");
_image.DrawMarker(predictX, predictY, CvColor.Purple, MarkerStyle.CircleLine);
_rectToTrack = CheckROIBounds(new CvRect(predictX - Mathf.FloorToInt(_rectToTrack.Width / 2),
predictY - Mathf.FloorToInt(_rectToTrack.Height / 2),
_rectToTrack.Width, _rectToTrack.Height));
_image.DrawRect(_rectToTrack, CvColor.Purple);
}
if (trackWindowFlag)
Cv.ShowImage("Image", _image);
}
/// <summary>
/// チェスボードコーナーの過度の四点を結ぶ四角形を描画します
/// </summary>
/// <param name="mat"></param>
/// <param name="pattern_size"></param>
/// <param name="corner"></param>
/// <param name="color"></param>
public static void DrawChessboardCornerFrame(CvMat mat, CvSize pattern_size, CvPoint2D32f[] corner, CvScalar color)
{
CvPoint2D32f[] points = new CvPoint2D32f[] { corner[0], corner[pattern_size.Width - 1], corner[pattern_size.Width * pattern_size.Height - 1], corner[(pattern_size.Height - 1) * pattern_size.Width] };
mat.DrawPolyLine(new CvPoint[][] { points.Select(p => new CvPoint((int)Math.Round(p.X), (int)Math.Round(p.Y))).ToArray() }, true, color, 1, LineType.AntiAlias);
}
/// <summary>
/// チェスボードコーナーの過度の四点を結ぶ四角形を描画します
/// </summary>
/// <param name="mat"></param>
/// <param name="pattern_size"></param>
/// <param name="corner"></param>
/// <param name="color"></param>
public static void DrawChessboardCornerFrame(CvMat mat, CvSize pattern_size, CvPoint2D32f[] corner, CvScalar color)
{
CvPoint2D32f[] points = new CvPoint2D32f[] { corner[0], corner[pattern_size.Width - 1], corner[pattern_size.Width * pattern_size.Height - 1], corner[(pattern_size.Height - 1) * pattern_size.Width] };
mat.DrawPolyLine(new CvPoint[][] { points.Select(p => new CvPoint((int)Math.Round(p.X), (int)Math.Round(p.Y))).ToArray() }, true, color, 1, LineType.AntiAlias);
}
// Use the CamShift algorithm to track to base histogram throughout the
// succeeding frames
void CalculateCamShift(CvMat _image)
{
CvMat _backProject = CalculateBackProjection(_image, _histogramToTrack);
// Create convolution kernel for erosion and dilation
IplConvKernel elementErode = Cv.CreateStructuringElementEx(10, 10, 5, 5, ElementShape.Rect, null);
IplConvKernel elementDilate = Cv.CreateStructuringElementEx(4, 4, 2, 2, ElementShape.Rect, null);
// Try eroding and then dilating the back projection
// Hopefully this will get rid of the noise in favor of the blob objects.
Cv.Erode(_backProject, _backProject, elementErode, 1);
Cv.Dilate(_backProject, _backProject, elementDilate, 1);
if (backprojWindowFlag)
{
Cv.ShowImage("Back Projection", _backProject);
}
// Parameters returned by Camshift algorithm
CvBox2D _outBox;
CvConnectedComp _connectComp;
// Set the criteria for the CamShift algorithm
// Maximum 10 iterations and at least 1 pixel change in centroid
CvTermCriteria term_criteria = Cv.TermCriteria(CriteriaType.Iteration | CriteriaType.Epsilon, 10, 1);
// Draw object center based on Kalman filter prediction
CvMat _kalmanPrediction = _kalman.Predict();
int predictX = Mathf.FloorToInt((float)_kalmanPrediction.GetReal2D(0, 0));
int predictY = Mathf.FloorToInt((float)_kalmanPrediction.GetReal2D(1, 0));
// Run the CamShift algorithm
if (Cv.CamShift(_backProject, _rectToTrack, term_criteria, out _connectComp, out _outBox) > 0)
{
// Use the CamShift estimate of the object center to update the Kalman model
CvMat _kalmanMeasurement = Cv.CreateMat(2, 1, MatrixType.F32C1);
// Update Kalman model with raw data from Camshift estimate
_kalmanMeasurement.Set2D(0, 0, _outBox.Center.X); // Raw X position
_kalmanMeasurement.Set2D(1, 0, _outBox.Center.Y); // Raw Y position
//_kalmanMeasurement.Set2D (2, 0, _outBox.Center.X - lastPosition.X);
//_kalmanMeasurement.Set2D (3, 0, _outBox.Center.Y - lastPosition.Y);
lastPosition.X = Mathf.FloorToInt(_outBox.Center.X);
lastPosition.Y = Mathf.FloorToInt(_outBox.Center.Y);
_kalman.Correct(_kalmanMeasurement); // Correct Kalman model with raw data
// CamShift function returns two values: _connectComp and _outBox.
// _connectComp contains is the newly estimated position and size
// of the region of interest. This is passed into the subsequent
// call to CamShift
// Update the ROI rectangle with CamShift's new estimate of the ROI
_rectToTrack = CheckROIBounds(_connectComp.Rect);
// Draw a rectangle over the tracked ROI
// This method will draw the rectangle but won't rotate it.
_image.DrawRect(_rectToTrack, CvColor.Aqua);
_image.DrawMarker(predictX, predictY, CvColor.Aqua);
// _outBox contains a rotated rectangle esimating the position, size, and orientation
// of the object we want to track (specified by the initial region of interest).
// We then take this estimation and draw a rotated bounding box.
// This method will draw the rotated rectangle
rotatedBoxToTrack = _outBox;
// Draw a rotated rectangle representing Camshift's estimate of the
// object's position, size, and orientation.
_image.DrawPolyLine(rectangleBoxPoint(_outBox.BoxPoints()), true, CvColor.Red);
}
else
{
//Debug.Log ("Object lost by Camshift tracker");
_image.DrawMarker(predictX, predictY, CvColor.Purple, MarkerStyle.CircleLine);
_rectToTrack = CheckROIBounds(new CvRect(predictX - Mathf.FloorToInt(_rectToTrack.Width / 2),
predictY - Mathf.FloorToInt(_rectToTrack.Height / 2),
_rectToTrack.Width, _rectToTrack.Height));
_image.DrawRect(_rectToTrack, CvColor.Purple);
}
if (trackWindowFlag)
{
Cv.ShowImage("Image", _image);
}
}
