bool AdaptiveHistogramCamshift::ComputeCamshift(const IplImage* hue, const IplImage* mask)
{
// Compute backproject
cvCalcBackProject(&hue, m_imgBackproject, m_hist);
cvAnd(m_imgBackproject, mask, m_imgBackproject, 0);
// Init velocity
m_trackPosTwoFramesBack = cvPoint(static_cast<int>(m_trackBox.center.x),
static_cast<int>(m_trackBox.center.y));
m_trackAreaTwoFramesBack = m_trackBox.size.width * m_trackBox.size.height;
// DEBUG track window area
//printf("track wnd area: %f\n", m_trackBox.size.width * m_trackBox.size.height);
// Compute camshift this frame
CvConnectedComp trackComp;
assert((m_trackWindow.height > 0) && (m_trackWindow.width > 0));
CvBox2D trackBox;
const int camShiftRes = cvCamShift(m_imgBackproject,
m_trackWindow,
cvTermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1),
&trackComp,
&trackBox);
if (camShiftRes >= 0)
{
m_trackBox = trackBox;
m_trackCompRect = trackComp.rect;
return true;
}
else
{
return false;
}
}
CvRect combi_track(IplImage * pImg,KalmanFilter &kfilter)
{
CvRect predrect=kfilter.predictionReport(prevHandRect);
//if((predrect.x<0)||(predrect.y<0)||((predrect.x+predrect.width)>pImg->width)||((predrect.y+predrect.height)>pImg->height))
// return NULL;
CvConnectedComp components;
// Create a new hue image
updateHueImage(pImg);
// Create a probability image based on the hand histogram
cvCalcBackProject( &pHueImg, pProbImg, pHist );
cvAnd( pProbImg, pMask, pProbImg, 0 );
//cvSetImageROI(pProbImg,predrect);
// Use CamShift to find the center of the new hand probability
if(!((predrect.x<0)||(predrect.y<0)||((predrect.x+predrect.width)>pImg->width)||((predrect.y+predrect.height)>pImg->height))) {
cvCamShift( pProbImg, predrect, cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),&components, handBox );
// Update hand location and angle
prevHandRect = components.rect;
}
else
//cvCamShift( pProbImg, prevHandRect, cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),&components, handBox );
prevHandRect.x=-1;
//if(!pImg->origin)
// handBox->angle = -handBox->angle;
//cvResetImageROI(pProbImg);
return prevHandRect;
}
void CamShift::DoExternal(IplImage* image)
{
ASSERT(m_pProbProv);
ASSERT(m_comp.rect.width != 0 && m_comp.rect.height != 0);
CvRect rect = m_comp.rect;
if( rect.x < 0 )
rect.x = 0;
if( rect.x + rect.width > m_img_width )
rect.width = m_img_width - rect.x;
if( rect.y < 0 )
rect.y = 0;
if( rect.y + rect.height > m_img_height )
rect.height = m_img_height - rect.y;
CRect roi;
roi.left = m_comp.rect.x-m_comp.rect.width/2;
roi.right = roi.left+m_comp.rect.width*2;
roi.top = m_comp.rect.y-m_comp.rect.height/2;
roi.bottom = roi.top+m_comp.rect.height*2;
m_pProbProv->CreateMap(image, m_prob_map, roi);
cvCamShift(m_prob_map, rect,
cvTermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1),
&m_comp, &m_box );
if( m_comp.rect.width == 0 || m_comp.rect.height == 0 )
m_comp.rect = rect; // do not allow tracker to loose the object
}
CvBox2D CamShiftPatch::getTrackBox(CvScalar maskRange, CvHistogram *hist)
{
IplImage* backproject = cvCreateImage(cvGetSize(originImage), 8, 1);//反投影空間，單通道
IplImage* hue = 0;
hue = cvCreateImage(cvGetSize(originImage), 8, 1);
IplImage *mask = getInRangeMask(maskRange, hue);
cvCalcBackProject(&hue, backproject, hist); //使用back project方法 ，計算hue的反投影圖
cvAnd(backproject, mask, backproject, 0); // 將backproject 與mask 做AND 運算 再放到backproject
CvConnectedComp track_comp;
CvBox2D track_box; // tracking返回的區域box，帶角度
CvRect zero;
zero.x = 0; zero.y = 0; zero.width = 320; zero.height = 240;
track_window = zero;
for (int i = 0; i < 10; i++)
{
cvCamShift(
backproject, //色彩概率分佈圖像
track_window, //Search Window的初始值
cvTermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1),//用來判斷搜尋是否停止的一個標準
&track_comp, //保存運算結果,包括新的Search Window的位置和面積
&track_box //包含被跟蹤物體的最小矩形
);
track_window = track_comp.rect;
}
cvReleaseImage(&backproject);
cvReleaseImage(&hue);
cvReleaseImage(&mask);
return track_box;
}
CamShift::Box CamShift::Track(const ImgBgr& img)
{
cvCopy(ImgIplImage(img), image, 0 );
cvCvtColor( image, hsv, CV_BGR2HSV );
cvFlip(hsv,hsv,0);
int _vmin = vmin, _vmax = vmax;
cvInRangeS( hsv, cvScalar(0,smin,MIN(_vmin,_vmax),0),
cvScalar(180,256,MAX(_vmin,_vmax),0), mask );
cvSplit( hsv, hue, 0, 0, 0 );
cvCalcBackProject( &hue, backproject, hist );
//cvSaveImage("backproject.bmp", backproject);
cvAnd( backproject, mask, backproject, 0 );
//cvSaveImage("backproject.bmp", backproject);
cvCamShift( backproject, track_window,
cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),
&track_comp, &track_box );
track_window = track_comp.rect;
Box result;
result.angle= track_box.angle;
result.center.x= static_cast<LONG>( track_box.center.x );
result.center.y= static_cast<LONG>( img.Height()-track_box.center.y-1 );
result.size.cy = static_cast<LONG>( track_box.size.width );
result.size.cx = static_cast<LONG>( track_box.size.height );
return result;
}
void WebCamData::trackFace() {
CvConnectedComp comps;
updateHugeImage(d->data);
cvCalcBackProject(&d->hueImage, d->prob, d->histogram);
cvAnd(d->prob, d->mask, d->prob, 0);
CvBox2D box;
cvCamShift(d->prob, d->faceRect,
cvTermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1), &comps,
&box);
d->faceRect = comps.rect;
int radius = cvRound((d->faceRect.width + d->faceRect.height) * 0.25);
CvPoint center;
center.x = cvRound(d->faceRect.x + d->faceRect.width * 0.5);
center.y = cvRound(d->faceRect.y + d->faceRect.height * 0.5);
/*
qDebug() << Q_FUNC_INFO
<< comps.rect.x
<< comps.rect.y
<< comps.rect.width
<< comps.rect.height
<< box.angle
<< center.x
<< center.y
<< radius;
*/
d->dataMap.clear();
d->dataMap["z"] = QVariant(radius);
d->dataMap["x"] = QVariant(center.x);
d->dataMap["y"] = QVariant(center.y);
d->dataMap["angle"] = QVariant(box.angle);
Q_EMIT dataReady();
}
int
camshift(const IplImage* next, TrackObject* obj)
//Input: next : Next Frame, obj : offline tracking object
{
IplImage* img = cvCloneImage(next);
IplImage* hsv_next = cvCreateImage(cvGetSize(next), IPL_DEPTH_8U, 3); //Size changes. No global or static
IplImage* h_next_8 = cvCreateImage(cvGetSize(next), IPL_DEPTH_8U, 1); //Size changes. No global or static
IplImage* h_next = cvCreateImage(cvGetSize(next), IPL_DEPTH_32F, 1);
IplImage* img_bp = cvCreateImage(cvGetSize(next), IPL_DEPTH_32F, 1);
CvConnectedComp track_comp;
//CvRect search_window = CALC_RECT(CALC_RECT_CENTER_X(eye), CALC_RECT_CENTER_Y(eye), WINDOW_W, WINDOW_H);
//Conversion
cvCvtColor(next, hsv_next, CV_BGR2HSV);
cvSplit(hsv_next, h_next_8, 0, 0, 0);
cvConvertScale(h_next_8, h_next, 1, 0);
cvCalcBackProject(&h_next, img_bp, obj->hist);
int iteration;
iteration = cvCamShift(img_bp, obj->track_window,
cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, MAX_ITER, EPSILON),
&track_comp, &obj->track_box);
obj->track_window = track_comp.rect;
cvReleaseImage(&img_bp);
cvReleaseImage(&h_next);
cvReleaseImage(&h_next_8);
cvReleaseImage(&hsv_next);
cvReleaseImage(&img);
return(iteration);
}
RotatedRect CamShift( const Mat& probImage, Rect& window,
TermCriteria criteria )
{
CvConnectedComp comp;
CvBox2D box;
CvMat _probImage = probImage;
cvCamShift(&_probImage, window, (CvTermCriteria)criteria, &comp, &box);
window = comp.rect;
return RotatedRect(Point2f(box.center), Size2f(box.size), box.angle);
}
void CamShiftPlugin::ProcessStatic
( int i, ImagePlus *img, ImagePlus *oimg, int *hsizes, CvTermCriteria criteria,
IplImage** &planes, CvHistogram* &hist, IplImage* &backproject, CvRect &orect, CvPoint &ocenter, CvRect &searchwin, CvMat* &rotation, CvMat* &shift, bool oready){
if (hist && hist->mat.dim[0].size!=hsizes[0])
cvReleaseHist(&hist);
if( !hist )
hist = cvCreateHist( 3, hsizes, CV_HIST_ARRAY, NULL, 0);
if( !backproject )
backproject = cvCreateImage( cvGetSize(img->orig), IPL_DEPTH_8U, 1 );
if( !planes ){
planes = (IplImage**) malloc(3 * sizeof(IplImage*));
for (int p=0; p<3; p++)
planes[p] = cvCreateImage( cvGetSize(img->orig), 8, 1 );
}
if (!rotation)
rotation = cvCreateMat(2,3,CV_32FC1);
if (!shift)
shift = cvCreateMat(2,1,CV_32FC1);
if (!oready){
orect = cvBoundingRect(oimg->contourArray[i],1);
cvCvtPixToPlane( oimg->orig, planes[0], planes[1], planes[2], 0 );
for (int p=0; p<3; p++)
cvSetImageROI(planes[p],orect);
cvCalcHist( planes, hist, 0, NULL );
cvNormalizeHist(hist, 255);
for (int p=0; p<3; p++)
cvResetImageROI(planes[p]);
searchwin = orect; //cvRect(0,0,img->orig->width, img->orig->height);
ocenter = cvPoint(orect.x+orect.width/2, orect.y+orect.height/2);
}
//The following checks shouldn't be needed.
RestrictRect(searchwin, cvRect(0,0,backproject->width,backproject->height));
cvCvtPixToPlane( img->orig, planes[0], planes[1], planes[2], 0 );
cvCalcBackProject( planes, backproject, hist );
CvBox2D track_box;
CvConnectedComp track_comp;
cvCamShift( backproject, searchwin,
criteria,
&track_comp, &track_box );
searchwin = track_comp.rect;
cvmSet(shift,0,0,track_box.center.x - ocenter.x);
cvmSet(shift,1,0,track_box.center.y - ocenter.y);
// shift->data.fl[0] = track_box.center.x - ocenter.x;
// shift->data.fl[1] = track_box.center.y - ocenter.y;
cv2DRotationMatrix(track_box.center, track_box.angle, 1.0, rotation);
cvTransform(oimg->contourArray[i],img->contourArray[i],rotation,shift);
// CvMat *ofm = FeatPointsToMat(oimg->feats[i]);
// Cvmat *fm = FeatPointsToMat(img->feats[i]);
// cvTransform(ofm,img->contourArray[i],rotation,shift);
TransformFeatPoints(oimg->feats[i], img->feats[i], rotation, shift);
}
void HandDetect::skinDetect()
{
setImage();
cvFlip(image, image, 1);
hsv = cvCreateImage(cvGetSize(image), 8, 3);
msk = cvCreateImage(cvGetSize(image), 8, 1);
hue = cvCreateImage(cvGetSize(image), 8, 1);
backproject1 = cvCreateImage(cvGetSize(image), 8, 1);
backproject2 = cvCreateImage(cvGetSize(image), 8, 1);
cvCvtColor(image, hsv, CV_RGB2HSV);
cvInRangeS(hsv, cvScalar(0, smin, MIN(vmin, vmax), 0), cvScalar(180, 256, MAX(vmin, vmax), 0), msk);
cvSplit(hsv, hue, 0, 0, 0);
cvCalcBackProject(&hue, backproject1, hist1);
cvCalcBackProject(&hue, backproject2, hist2);
cvThreshold(backproject1, backproject1, 50, 255, CV_THRESH_BINARY | CV_THRESH_OTSU);
cvThreshold(backproject2, backproject2, 50, 255, CV_THRESH_BINARY | CV_THRESH_OTSU);
cvOr(backproject1, backproject2, backproject, 0);
cvErode(backproject, backproject, 0, 1);
cvDilate(backproject, backproject, 0, 1);
cvAnd(backproject, msk, backproject, 0);
if(track_box.center.x!=-1&&track_box.center.y!=-1)
preCen=cvPoint(handCen.x, handCen.y);
else
preCen=cvPoint(0,0);
cvCamShift(backproject, track_window, cvTermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1), &track_comp, &track_box);
if(track_comp.rect.height>0&&track_comp.rect.width>0)
track_window = track_comp.rect;
else
{
track_box.center.x=-1;
track_box.center.y=-1;
}
cvReleaseImage(&hsv);
cvReleaseImage(&msk);
cvReleaseImage(&hue);
cvReleaseImage(&backproject1);
cvReleaseImage(&backproject2);
}
int track(camshift * cs, IplImage * img, CvBox2D * fBox)
{
CvConnectedComp components;
updateHueImage(cs, img);
cvCalcBackProject( &cs->hueImg, cs->probImg, cs->hist );
cvAnd( cs->probImg, cs->mask, cs->probImg, 0 );
CvSize size = cvGetSize(cs->probImg);
// printf("%d %d %d %d\n", cs->prevFaceRect.x, cs->prevFaceRect.y, cs->prevFaceRect.width, cs->prevFaceRect.height);
if (cs->prevFaceRect.x <= 0) {
return 0;
}
if (cs->prevFaceRect.x > size.width) {
return 0;
}
if (cs->prevFaceRect.y <= 0) {
return 0;
}
if (cs->prevFaceRect.y > size.height) {
return 0;
}
if (cs->prevFaceRect.x + cs->prevFaceRect.width > size.width) {
return 0;
}
if (cs->prevFaceRect.y + cs->prevFaceRect.height > size.height) {
return 0;
}
if (cs->prevFaceRect.width <= 0) {
return 0;
}
if (cs->prevFaceRect.height <= 0) {
return 0;
}
cvCamShift( cs->probImg, cs->prevFaceRect,
cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),
&components, &cs->faceBox );
cs->prevFaceRect = components.rect;
cs->faceBox.angle = -cs->faceBox.angle;
*fBox = cs->faceBox;
return 1;
}
//////////////////////////////////
// track()
//
CvBox2D track(camshift * cs, IplImage * pImg)
{
CvConnectedComp components;
// Create a new hue image
updateHueImage(cs, pImg);
// Create a probability image based on the face histogram
cvCalcBackProject( &cs->pHueImg, cs->pProbImg, cs->pHist );
cvAnd( cs->pProbImg, cs->pMask, cs->pProbImg, 0 );
// Use CamShift to find the center of the new face probability
CvSize size = cvGetSize(cs->pProbImg);
if (cs->prevFaceRect.x < 0) {
cs->prevFaceRect.x = 0;
}
if (cs->prevFaceRect.x >= size.width) {
cs->prevFaceRect.x = size.width - 1;
}
if (cs->prevFaceRect.y < 0) {
cs->prevFaceRect.y = 0;
}
if (cs->prevFaceRect.y >= size.height) {
cs->prevFaceRect.y = size.height - 1;
}
if (cs->prevFaceRect.x + cs->prevFaceRect.width > size.width) {
cs->prevFaceRect.width = size.width - cs->prevFaceRect.x;
}
if (cs->prevFaceRect.y + cs->prevFaceRect.height > size.height) {
cs->prevFaceRect.height = size.height - cs->prevFaceRect.y;
}
cvCamShift( cs->pProbImg, cs->prevFaceRect,
cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),
&components, &cs->faceBox );
// Update face location and angle
cs->prevFaceRect = components.rect;
cs->faceBox.angle = -cs->faceBox.angle;
return cs->faceBox;
}
/* Given an image and tracked object, return box position. */
CvBox2D FaceBl0r::camshift_track_face (IplImage* image, TrackedObj* obj) {
CvConnectedComp components;
//create a new hue image
update_hue_image(image, obj);
//create a probability image based on the face histogram
cvCalcBackProject(&obj->hue, obj->prob, obj->hist);
cvAnd(obj->prob, obj->mask, obj->prob, 0);
//use CamShift to find the center of the new face probability
cvCamShift(obj->prob, obj->prev_rect,
cvTermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1),
&components, &obj->curr_box);
//update face location and angle
obj->prev_rect = components.rect;
obj->curr_box.angle = -obj->curr_box.angle;
return obj->curr_box;
}
//////////////////////////////////
// track()
//
CvRect camshift_track(IplImage * pImg)
{
CvConnectedComp components;
// Create a new hue image
updateHueImage(pImg);
// Create a probability image based on the hand histogram
cvCalcBackProject( &pHueImg, pProbImg, pHist );
cvAnd( pProbImg, pMask, pProbImg, 0 );
//cvSetImageROI(pProbImg,predrect);
// Use CamShift to find the center of the new hand probability
cvCamShift( pProbImg, prevHandRect2, cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),&components, handBox );
// Update hand location and angle
prevHandRect2 = components.rect;
//if(!pImg->origin)
// handBox->angle = -handBox->angle;
//cvResetImageROI(pProbImg);
return prevHandRect2;
}
void BoatDetecting::startTrackObject(){
cvInRangeS(hsv, cvScalar(0, smin, MIN(vmin, vmax), 0), cvScalar(180, 256, MAX(vmin, vmax), 0), mask);
// 10,256,30
cvSplit(hsv, hue, 0, 0, 0);
if (!isTrackingInitialized){ // 如果跟踪窗口未初始化
float max_val = 0.f;
cvSetImageROI(hue, selection);
cvSetImageROI(mask, selection);
cvCalcHist(&hue, hist, 0, mask);
cvGetMinMaxHistValue(hist, 0, &max_val, 0, 0);
cvConvertScale(hist->bins, hist->bins, max_val ? 255. / max_val : 0., 0);
cvResetImageROI(hue);
cvResetImageROI(mask);
trackWindow = selection;
isTrackingInitialized = true;
}
cvCalcBackProject(&hue, backproject, hist);
//cvShowImage("Hue Channel",backproject);
cvAnd(backproject, mask, backproject, 0);
//if (trackWindow.x + trackWindow.width/2< allfWidth &&trackWindow.y + trackWindow.height/2< allfHeight &&trackWindow.x>0)
if (trackWindow.x + trackWindow.width< allfWidth &&trackWindow.y + trackWindow.height< allfHeight &&trackWindow.x>0)
cvCamShift(backproject, trackWindow, cvTermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 20, 1), &trackComp, 0);//初始化跟踪窗口以后直接用trackWindow做跟踪，每帧都会更新
//if (trackComp.rect.width<90 && trackComp.rect.y<200){
// trackWindow = trackComp.rect;
//}
//if (trackComp.rect.y>200)
//{
// trackWindow = trackComp.rect;
//}
trackWindow = trackComp.rect;
}
//////////////////////////////////
// track()
//
CvBox2D track(IplImage * pImg)
{
CvConnectedComp components;
// Create a new hue image
updateHueImage(pImg);
// Create a probability image based on the face histogram
cvCalcBackProject( &pHueImg, pProbImg, pHist );
cvAnd( pProbImg, pMask, pProbImg, 0 );
// Use CamShift to find the center of the new face probability
cvCamShift( pProbImg, prevFaceRect,
cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),
&components, &faceBox );
// Update face location and angle
prevFaceRect = components.rect;
faceBox.angle = -faceBox.angle;
return faceBox;
}
CvConnectedComp* CAMShift::track(const Image* image, const Mask* probabilisticMap)
{
if (!m_trackingHist)
return NULL;
//Obtain probabilistic image from backProject of histogram
Mask* probimage = m_trackingHist->calcBackProjection(image);
if (probabilisticMap)
(*probimage) = (*probabilisticMap);
if ((m_lastPostition.width < 0) || (m_lastPostition.height < 0)
|| (m_lastPostition.x > image->width()) || (m_lastPostition.y > image->height()))
return &m_components;
//cvTermCriteria with CV_TERMCRIT_ITER specifies number of iteratios until center of mass found
//cvTermCriteria with CV_TERMCRIT_EPS specifies the max error of the result
cvCamShift(probimage->cvImage(), m_lastPostition, cvTermCriteria(CV_TERMCRIT_EPS, 256, .001l), &m_components, m_box);
//Update lastPosition
m_lastPostition = m_components.rect;
return &m_components;
}
void CamShift::Track(IplImage *frame, CvRect &selection, bool calc_hist)
{
int i, bin_w, c;
cvCvtColor( frame, _hsv, CV_BGR2HSV );
cvInRangeS( _hsv, cvScalar(0,_smin,MIN(_vmin,_vmax),0),
cvScalar(180,256,MAX(_vmin,_vmax),0), _mask );
cvSplit( _hsv, _hue, 0, 0, 0 );
if(calc_hist)
{
float max_val = 0.f;
cvSetImageROI( _hue, selection );
cvSetImageROI( _mask, selection );
cvCalcHist( &_hue, _hist, 0, _mask );
cvGetMinMaxHistValue( _hist, 0, &max_val, 0, 0 );
cvConvertScale( _hist->bins, _hist->bins, max_val ? 255. / max_val : 0., 0 );
cvResetImageROI( _hue );
cvResetImageROI( _mask );
_track_window = selection;
}
cvCalcBackProject( &_hue, _backproject, _hist );
cvAnd( _backproject, _mask, _backproject, 0 );
cvCamShift( _backproject, _track_window,
cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),
&_track_comp, &_track_box );
_track_window = _track_comp.rect;
if( frame->origin )
_track_box.angle = -_track_box.angle;
selection = cvRect(_track_box.center.x-_track_box.size.width/2, _track_box.center.y-_track_box.size.height/2,
selection.width, selection.height);
}
CvBox2D *MultiCamshiftUI::track(IplImage **images, bool show_ui, bool show_backprojections) {
for (int camera=0; camera<n_cameras; camera++) {
/* Calculate the backprojection, in the original (YUV) colorspace */
cvCvtPixToPlane(images[camera], planes[0], planes[1], planes[2], 0);
cvCalcBackProject(planes, backprojection, histograms[camera]);
if (show_ui && show_backprojections) {
/* Make a YUV version of the output, for display */
gray_to_yuv(backprojection, yuv_backprojections[camera]);
}
if (search_windows[camera].width > 0 && search_windows[camera].height > 0) {
/* Use the CAMSHIFT algorithm to search for the object of interest */
CvConnectedComp comp;
cvCamShift(backprojection, search_windows[camera],
cvTermCriteria(CV_TERMCRIT_ITER | CV_TERMCRIT_EPS, 20, 1),
&comp, &results[camera]);
search_windows[camera] = comp.rect;
if (results[camera].size.width > 0 &&
results[camera].size.height > 0) {
/* We found an interesting object, draw it if applicable */
if (show_ui)
drawResults(camera, images[camera]);
}
else {
/* We lost tracking, expand the search window */
search_windows[camera].x = 0;
search_windows[camera].y = 0;
search_windows[camera].width = image_size.width;
search_windows[camera].height = image_size.height;
}
}
}
if (sample_from_sample_square) {
cvSetImageROI(images[sample_square_camera], sample_square);
cvSetImageROI(planes[0], sample_square);
cvSetImageROI(planes[1], sample_square);
cvSetImageROI(planes[2], sample_square);
cvCvtPixToPlane(images[sample_square_camera], planes[0], planes[1], planes[2], 0);
cvCalcHist(planes, histograms[sample_square_camera], 1);
cvResetImageROI(images[sample_square_camera]);
cvResetImageROI(planes[0]);
cvResetImageROI(planes[1]);
cvResetImageROI(planes[2]);
/* Also set the windowIn to the sampling rectangle, to point CAMSHIFT at
* what we're interested in.
*/
search_windows[sample_square_camera] = sample_square;
}
if (show_ui) {
/* Tile cameras horizontally, with original image on
* top and backprojection on bottom.
*/
IplImage* view_grid[n_cameras * 2];
int num_views = 0;
for (int i=0; i<n_cameras; i++)
view_grid[num_views++] = images[i];
if (show_backprojections) {
for (int i=0; i<n_cameras; i++)
view_grid[num_views++] = yuv_backprojections[i];
}
if (draw_sample_square) {
cvRectangle(images[sample_square_camera], cvPoint(sample_square.x-1, sample_square.y-1),
cvPoint(sample_square.x + sample_square.width + 1, sample_square.y + sample_square.width + 1),
CV_RGB(128,128,255), 1);
}
cv_sdl_show_yuv_tiles(view_grid, num_views, n_cameras);
}
return results;
}
//--------------------------------------------------------------------------------
int ContourFinder::findContours( ofxCvGrayscaleImage& input,
int minArea,
int maxArea,
int nConsidered,
bool bFindHoles,
bool bUseApproximation) {
reset();
// opencv will clober the image it detects contours on, so we want to
// copy it into a copy before we detect contours. That copy is allocated
// if necessary (necessary = (a) not allocated or (b) wrong size)
// so be careful if you pass in different sized images to "findContours"
// there is a performance penalty, but we think there is not a memory leak
// to worry about better to create mutiple contour finders for different
// sizes, ie, if you are finding contours in a 640x480 image but also a
// 320x240 image better to make two ContourFinder objects then to use
// one, because you will get penalized less.
if( inputCopy.width == 0 ) {
inputCopy.allocate( input.width, input.height );
inputCopy = input;
} else {
if( inputCopy.width == input.width && inputCopy.height == input.height ) {
inputCopy = input;
} else {
// we are allocated, but to the wrong size --
// been checked for memory leaks, but a warning:
// be careful if you call this function with alot of different
// sized "input" images!, it does allocation every time
// a new size is passed in....
//inputCopy.clear();
inputCopy.allocate( input.width, input.height );
inputCopy = input;
}
}
CvSeq* contour_list = NULL;
contour_storage = cvCreateMemStorage( 1000 );
storage = cvCreateMemStorage( 1000 );
CvContourRetrievalMode retrieve_mode
= (bFindHoles) ? CV_RETR_LIST : CV_RETR_EXTERNAL;
teste = inputCopy.getCvImage();
cvFindContours( teste, contour_storage, &contour_list,
sizeof(CvContour), retrieve_mode, bUseApproximation ? CV_CHAIN_APPROX_SIMPLE : CV_CHAIN_APPROX_NONE );
CvSeq* contour_ptr = contour_list;
nCvSeqsFound = 0;
// put the contours from the linked list, into an array for sorting
while( (contour_ptr != NULL) ) {
float area = fabs( cvContourArea(contour_ptr, CV_WHOLE_SEQ) );
if( (area > minArea) && (area < maxArea) ) {
if (nCvSeqsFound < TOUCH_MAX_CONTOUR_LENGTH){
cvSeqBlobs[nCvSeqsFound] = contour_ptr; // copy the pointer
nCvSeqsFound++;
}
}
contour_ptr = contour_ptr->h_next;
}
// sort the pointers based on size
if( nCvSeqsFound > 0 ) {
qsort( cvSeqBlobs, nCvSeqsFound, sizeof(CvSeq*), qsort_carea_compare);
}
// now, we have nCvSeqsFound contours, sorted by size in the array
// cvSeqBlobs let's get the data out and into our structures that we like
for( int i = 0; i < MIN(nConsidered, nCvSeqsFound); i++ ) {
blobs.push_back( Blob() );
float area = cvContourArea( cvSeqBlobs[i], CV_WHOLE_SEQ );
cvMoments( cvSeqBlobs[i], myMoments );
// this is if using non-angle bounding box
CvRect rect = cvBoundingRect( cvSeqBlobs[i], 0 );
blobs[i].boundingRect.x = rect.x;
blobs[i].boundingRect.y = rect.y;
blobs[i].boundingRect.width = rect.width;
blobs[i].boundingRect.height = rect.height;
cvCamShift(teste, rect, cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ), &track_comp, &track_box);
// this is for using angle bounding box
CvBox2D32f box;
box = cvMinAreaRect2( cvSeqBlobs[i] );
blobs[i].angleBoundingRect.x = box.center.x;
blobs[i].angleBoundingRect.y = box.center.y;
blobs[i].angleBoundingRect.width = box.size.height;
blobs[i].angleBoundingRect.height = box.size.width;
blobs[i].angle = box.angle;
// assign other parameters
blobs[i].area = fabs(area);
blobs[i].hole = area < 0 ? true : false;
blobs[i].length = cvArcLength(cvSeqBlobs[i]);
blobs[i].centroid.x = (int) (myMoments->m10 / myMoments->m00);
blobs[i].centroid.y = (int) (myMoments->m01 / myMoments->m00);
blobs[i].lastCentroid.x = (int) 0;
blobs[i].lastCentroid.y = (int) 0;
// get the points for the blob:
CvPoint pt;
CvSeqReader reader;
cvStartReadSeq( cvSeqBlobs[i], &reader, 0 );
for( int j=0; j < min(TOUCH_MAX_CONTOUR_LENGTH, cvSeqBlobs[i]->total); j++ ) {
CV_READ_SEQ_ELEM( pt, reader );
blobs[i].pts.push_back( ofPoint((float)pt.x, (float)pt.y) );
}
blobs[i].nPts = blobs[i].pts.size();
}
nBlobs = blobs.size();
// Free the storage memory.
// Warning: do this inside this function otherwise a strange memory leak
if( contour_storage != NULL ) { cvReleaseMemStorage(&contour_storage); }
if( storage != NULL ) { cvReleaseMemStorage(&storage); }
return nBlobs;
}
t_jit_err cv_jit_shift_matrix_calc(t_cv_jit_shift *x, void *inputs, void *outputs)
{
t_jit_err err=JIT_ERR_NONE;
long in_savelock = 0;
t_jit_matrix_info in_minfo;
void *in_matrix;
CvMat source;
CvRect rectangle;
CvBox2D box;
CvConnectedComp component;
CvPoint2D32f vertices[4];
float w,h,c,s;
//Get pointer to matrix
in_matrix = jit_object_method(inputs,_jit_sym_getindex,0);
if (x&&in_matrix)
{
//Lock the matrix
in_savelock = (long) jit_object_method(in_matrix,_jit_sym_lock,1);
//Make sure input is of proper format
jit_object_method(in_matrix,_jit_sym_getinfo,&in_minfo);
if(in_minfo.dimcount != 2)
{
err = JIT_ERR_MISMATCH_DIM;
goto out;
}
if(in_minfo.planecount != 1)
{
err = JIT_ERR_MISMATCH_PLANE;
goto out;
}
if(in_minfo.type != _jit_sym_char)
{
err = JIT_ERR_MISMATCH_TYPE;
goto out;
}
//Don't process if image is too small
if((in_minfo.dim[0] < 2)||(in_minfo.dim[1] < 2))
goto out;
//Calculate start rectangle:
rectangle = cvRect(x->rect[0],x->rect[1],x->rect[2]-x->rect[0],x->rect[3]-x->rect[1]);
CLIP_ASSIGN(rectangle.x,0,in_minfo.dim[0]-1);
CLIP_ASSIGN(rectangle.y,0,in_minfo.dim[1]-1);
CLIP_ASSIGN(rectangle.width,1,in_minfo.dim[0]-rectangle.x);
CLIP_ASSIGN(rectangle.height,1,in_minfo.dim[1]-rectangle.y);
//Convert Jitter matrix to OpenCV matrix
cvJitter2CvMat(in_matrix, &source);
//Calculate camshift
if(x->mode == 1) //Use camshift
cvCamShift(&source, rectangle, cvTermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS,(int)x->maxiters,x->epsilon), &component, &box );
else {
cvMeanShift(&source, rectangle, cvTermCriteria(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS,(int)x->maxiters,x->epsilon), &component);
box.angle = 90.f;
box.size = cvSize2D32f(component.rect.width, component.rect.height);
box.center = cvPoint2D32f((float)component.rect.x + (float)component.rect.width * 0.5f,(float)component.rect.y + (float)component.rect.height * 0.5f);
}
//Prepare output
//
jit_atom_setlong(&x->box[0],component.rect.x);
jit_atom_setlong(&x->box[1],component.rect.y);
jit_atom_setlong(&x->box[2],component.rect.x + component.rect.width);
jit_atom_setlong(&x->box[3],component.rect.y + component.rect.height);
x->rect[0]=component.rect.x;
x->rect[1]=component.rect.y;
x->rect[2]=component.rect.x + component.rect.width;
x->rect[3]=component.rect.y + component.rect.height;
//cvBoxPoints(box,vertices);
w = box.size.width * 0.5;
h = box.size.height * 0.5;
c = cos((box.angle - 90.f) * -0.01745329252);
s = sin((box.angle - 90.f) * -0.01745329252);
vertices[0].x = box.center.x - s*h - c*w;
vertices[0].y = box.center.y - c*h + s*w;
vertices[1].x = box.center.x - s*h + c*w;
vertices[1].y = box.center.y - c*h - s*w;
vertices[2].x = box.center.x + s*h + c*w;
vertices[2].y = box.center.y + c*h - s*w;
vertices[3].x = box.center.x + s*h - c*w;
vertices[3].y = box.center.y + c*h + s*w;
jit_atom_setlong(&x->frame[0],(long)vertices[0].x);
jit_atom_setlong(&x->frame[1],(long)vertices[0].y);
jit_atom_setlong(&x->frame[2],(long)vertices[1].x);
jit_atom_setlong(&x->frame[3],(long)vertices[1].y);
jit_atom_setlong(&x->frame[4],(long)vertices[2].x);
jit_atom_setlong(&x->frame[5],(long)vertices[2].y);
jit_atom_setlong(&x->frame[6],(long)vertices[3].x);
jit_atom_setlong(&x->frame[7],(long)vertices[3].y);
x->mass = (float)(component.area / 256.);
}
out:
jit_object_method(in_matrix,gensym("lock"),in_savelock);
return err;
}
//=========================================
CvRect camKalTrack(IplImage* frame, camshift_kalman_tracker& camKalTrk) {
//=========================================
if (!frame)
printf("Input frame empty!\n");
cvCopy(frame, camKalTrk.image, 0);
cvCvtColor(camKalTrk.image, camKalTrk.hsv, CV_BGR2HSV); // BGR to HSV
if (camKalTrk.trackObject) {
int _vmin = vmin, _vmax = vmax;
cvInRangeS(camKalTrk.hsv, cvScalar(0, smin, MIN(_vmin,_vmax), 0), cvScalar(180, 256, MAX(_vmin,_vmax), 0), camKalTrk.mask); // MASK
cvSplit(camKalTrk.hsv, camKalTrk.hue, 0, 0, 0); // HUE
if (camKalTrk.trackObject < 0) {
float max_val = 0.f;
boundaryCheck(camKalTrk.originBox, frame->width, frame->height);
cvSetImageROI(camKalTrk.hue, camKalTrk.originBox); // for ROI
cvSetImageROI(camKalTrk.mask, camKalTrk.originBox); // for camKalTrk.mask
cvCalcHist(&camKalTrk.hue, camKalTrk.hist, 0, camKalTrk.mask); //
cvGetMinMaxHistValue(camKalTrk.hist, 0, &max_val, 0, 0);
cvConvertScale(camKalTrk.hist->bins, camKalTrk.hist->bins, max_val ? 255. / max_val : 0., 0); // bin [0,255]
cvResetImageROI(camKalTrk.hue); // remove ROI
cvResetImageROI(camKalTrk.mask);
camKalTrk.trackWindow = camKalTrk.originBox;
camKalTrk.trackObject = 1;
camKalTrk.lastpoint = camKalTrk.predictpoint = cvPoint(camKalTrk.trackWindow.x + camKalTrk.trackWindow.width / 2,
camKalTrk.trackWindow.y + camKalTrk.trackWindow.height / 2);
getCurrState(camKalTrk.kalman, camKalTrk.lastpoint, camKalTrk.predictpoint);//input curent state
}
//(x,y,vx,vy),
camKalTrk.prediction = cvKalmanPredict(camKalTrk.kalman, 0);//predicton=kalman->state_post
camKalTrk.predictpoint = cvPoint(cvRound(camKalTrk.prediction->data.fl[0]), cvRound(camKalTrk.prediction->data.fl[1]));
camKalTrk.trackWindow = cvRect(camKalTrk.predictpoint.x - camKalTrk.trackWindow.width / 2, camKalTrk.predictpoint.y
- camKalTrk.trackWindow.height / 2, camKalTrk.trackWindow.width, camKalTrk.trackWindow.height);
camKalTrk.trackWindow = checkRectBoundary(cvRect(0, 0, frame->width, frame->height), camKalTrk.trackWindow);
camKalTrk.searchWindow = cvRect(camKalTrk.trackWindow.x - region, camKalTrk.trackWindow.y - region, camKalTrk.trackWindow.width + 2
* region, camKalTrk.trackWindow.height + 2 * region);
camKalTrk.searchWindow = checkRectBoundary(cvRect(0, 0, frame->width, frame->height), camKalTrk.searchWindow);
cvSetImageROI(camKalTrk.hue, camKalTrk.searchWindow);
cvSetImageROI(camKalTrk.mask, camKalTrk.searchWindow);
cvSetImageROI(camKalTrk.backproject, camKalTrk.searchWindow);
cvCalcBackProject( &camKalTrk.hue, camKalTrk.backproject, camKalTrk.hist ); // back project
cvAnd(camKalTrk.backproject, camKalTrk.mask, camKalTrk.backproject, 0);
camKalTrk.trackWindow = cvRect(region, region, camKalTrk.trackWindow.width, camKalTrk.trackWindow.height);
if (camKalTrk.trackWindow.height > 5 && camKalTrk.trackWindow.width > 5) {
// calling CAMSHIFT
cvCamShift(camKalTrk.backproject, camKalTrk.trackWindow, cvTermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1),
&camKalTrk.trackComp, &camKalTrk.trackBox);
/*cvMeanShift( camKalTrk.backproject, camKalTrk.trackWindow,
cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),
&camKalTrk.trackComp);*/
}
else {
camKalTrk.trackComp.rect.x = 0;
camKalTrk.trackComp.rect.y = 0;
camKalTrk.trackComp.rect.width = 0;
camKalTrk.trackComp.rect.height = 0;
}
cvResetImageROI(camKalTrk.hue);
cvResetImageROI(camKalTrk.mask);
cvResetImageROI(camKalTrk.backproject);
camKalTrk.trackWindow = camKalTrk.trackComp.rect;
camKalTrk.trackWindow = cvRect(camKalTrk.trackWindow.x + camKalTrk.searchWindow.x, camKalTrk.trackWindow.y
+ camKalTrk.searchWindow.y, camKalTrk.trackWindow.width, camKalTrk.trackWindow.height);
camKalTrk.measurepoint = cvPoint(camKalTrk.trackWindow.x + camKalTrk.trackWindow.width / 2, camKalTrk.trackWindow.y
+ camKalTrk.trackWindow.height / 2);
camKalTrk.realposition->data.fl[0] = camKalTrk.measurepoint.x;
camKalTrk.realposition->data.fl[1] = camKalTrk.measurepoint.y;
camKalTrk.realposition->data.fl[2] = camKalTrk.measurepoint.x - camKalTrk.lastpoint.x;
camKalTrk.realposition->data.fl[3] = camKalTrk.measurepoint.y - camKalTrk.lastpoint.y;
camKalTrk.lastpoint = camKalTrk.measurepoint;//keep the current real position
//measurement x,y
cvMatMulAdd( camKalTrk.kalman->measurement_matrix/*2x4*/, camKalTrk.realposition/*4x1*/,/*measurementstate*/0, camKalTrk.measurement );
cvKalmanCorrect(camKalTrk.kalman, camKalTrk.measurement);
cvRectangle(frame, cvPoint(camKalTrk.trackWindow.x, camKalTrk.trackWindow.y), cvPoint(camKalTrk.trackWindow.x
+ camKalTrk.trackWindow.width, camKalTrk.trackWindow.y + camKalTrk.trackWindow.height), CV_RGB(255,128,0), 4, 8, 0);
}
// set new selection if it exists
if (camKalTrk.selectObject && camKalTrk.selection.width > 0 && camKalTrk.selection.height > 0) {
cvSetImageROI(camKalTrk.image, camKalTrk.selection);
cvXorS(camKalTrk.image, cvScalarAll(255), camKalTrk.image, 0);
cvResetImageROI(camKalTrk.image);
}
return camKalTrk.trackWindow;
}
CvBox2D CamShiftIris::track( IplImage* image, CvRect selection, bool isIris){
CamShiftIris camshift;
select_object1=1;
track_object1=-1;
origin1=cvPoint(0,0);
///////////////////////////////
int i, bin_w, c;
//frame = cvQueryFrame( capture );
//
// frame=cvCloneImage(image);
// if( !frame )
// return 0;
if( image ){
/* allocate all the buffers */
// image = cvCreateImage( cvGetSize(frame), 8, 3 );
// image->origin = frame->origin;
hsv1 = cvCreateImage( cvGetSize(image), 8, 3 );
h = cvCreateImage( cvGetSize(image), 8, 1 );
s = cvCreateImage( cvGetSize(image), 8, 1 );
v = cvCreateImage( cvGetSize(image), 8, 1);
hue1 = cvCreateImage( cvGetSize(image), 8, 1 );
mask1 = cvCreateImage( cvGetSize(image), 8, 1 );
backproject1 = cvCreateImage( cvGetSize(image), 8, 1 );
hist1= cvCreateHist( 1, &hdims1, CV_HIST_ARRAY, &hranges1, 1 );
histimg1 = cvCreateImage( cvSize(320,200), 8, 3 );
cvZero( histimg1 );
}
cvCvtColor( image, hsv1, CV_BGR2HSV );
///////////////////Equalize v in hsv///////////
cvSplit( hsv1, h, s, v, 0 );
cvEqualizeHist(v,v);
cvMerge(h,s,v,0,hsv1);
///////////////////Equalize v in hsv///////////
if( track_object1 !=0 ){
int _vmin1 = vmin1, _vmax1 = vmax1;
cvInRangeS( hsv1, cvScalar(0,smin1,MIN(_vmin1,_vmax1),0),
cvScalar(180,256,MAX(_vmin1,_vmax1),0), mask1 );
cvSplit( hsv1, hue1, 0, 0, 0 );
if( track_object1 < 0 ){
float max_val = 0.f;
cvSetImageROI( hue1, selection );
cvSetImageROI( mask1, selection );
cvCalcHist( &hue1, hist1, 0, mask1 );
cvGetMinMaxHistValue( hist1, 0, &max_val, 0, 0 );
cvConvertScale( hist1->bins, hist1->bins, max_val ? 255. / max_val : 0., 0 );
cvResetImageROI( hue1 );
cvResetImageROI( mask1 );
track_window1 = selection;
track_object1 = 1;
cvZero( histimg1 );
bin_w = histimg1->width / hdims1;
for( i = 0; i < hdims1; i++ )
{
int val = cvRound( cvGetReal1D(hist1->bins,i)*histimg1->height/255 );
CvScalar color = camshift.hsvrgb(i*180.f/hdims1);
cvRectangle( histimg1, cvPoint(i*bin_w,histimg1->height),
cvPoint((i+1)*bin_w,histimg1->height - val),
color, -1, 8, 0 );
}
}
cvCalcBackProject( &hue1, backproject1, hist1);
cvAnd( backproject1, mask1, backproject1, 0 );
try{
cvCamShift( backproject1, track_window1,
cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),
&track_comp1, &track_box1 );
}catch(...){
cvReleaseImage(&hsv1);
cvReleaseImage(&h);
cvReleaseImage(&s);
cvReleaseImage(&v);
cvReleaseImage(&hue1);
cvReleaseImage(&mask1);
cvReleaseImage(&backproject1);
cvReleaseHist(&hist1);
cvReleaseImage(&histimg1);
}
track_window1 = track_comp1.rect;
if( backproject1_mode )
cvCvtColor( backproject1, image, CV_GRAY2BGR );
if( !image->origin )
track_box1.angle = -track_box1.angle;
if(isIris)
cvEllipseBox( image, track_box1, CV_RGB(255,0,0), 3, CV_AA, 0 );
}
cvShowImage( "CamShift Tracking", image );
//cvShowImage( "Histogram", histimg1 );
// c = cvWaitKey(10);
// if( (char) c == 27 )
// cout<<"esc pressed";
// //return; //break;
// switch( (char) c ){
// case 'b':
// backproject1_mode ^= 1;
// break;
// case 'c':
// track_object1 = 0;
// cvZero( histimg1 );
// break;
// case 'h':
// show_hist1^= 1;
// if( !show_hist1)
// cvDestroyWindow( "Histogram" );
// else
// cvNamedWindow( "Histogram", 1 );
// break;
// default:
// ;
// }
//cvReleaseImage(&image);
cvReleaseImage(&hsv1);
cvReleaseImage(&h);
cvReleaseImage(&s);
cvReleaseImage(&v);
cvReleaseImage(&hue1);
cvReleaseImage(&mask1);
cvReleaseImage(&backproject1);
cvReleaseHist(&hist1);
cvReleaseImage(&histimg1);
return track_box1;
}
static int foaCamShiftC1R( void* prm )
{
/* Some variables */
long lParam = (long)prm;
int Flvr = (lParam >> 4) & 0xf;
int depth = (Flvr == ATS_8U ? IPL_DEPTH_8U :
Flvr == ATS_8S ? IPL_DEPTH_8S : IPL_DEPTH_32F);
int Type = lParam & 0xf;
int Errors = 0;
CvTermCriteria criteria;
CvRect Window;
CvSize roi;
IplImage* src;
float alpha = 0;
int i;
int x, y;
float destOrientation = 0;
float destLen = 0;
float destWidth = 0;
float destArea = 0;
int destIters = 0;
static int read_param = 0;
/* Initialization global parameters */
if( !read_param )
{
read_param = 1;
trsiRead( &height, "512", "source array length" );
trsiRead( &width, "512", "source array width" );
trsiRead( &Length, "68", "oval length" );
trsiRead( &Width, "15", "oval width" );
trsiRead( &iter, "10", "iterations" );
trsiRead( &steps, "10", "steps" );
trssRead( &epsilon, "1", "epsilon" );
}
/* Initilization */
Window.x = width / 4;
Window.y = height / 4;
Window.width = width / 2;
Window.height = height / 2;
roi.width = width;
roi.height = height;
criteria.type = Type;
criteria.epsilon = epsilon;
criteria.maxIter = iter;
/* Allocating source arrays; */
src = cvCreateImage(roi, depth, 1);
assert(src);
for( alpha = -Pi / 2; alpha < Pi / 2; alpha += Pi / steps )
{
x = (int)(width / 2 + width / 8 * cos(alpha));
y = (int)(height / 2 + height / 8 * sin(alpha));
switch( Flvr )
{
case ATS_8U:
atsbInitEllipse( (uchar*)src->imageData,
roi.width,
roi.height,
src->widthStep,
x,
y,
Length,
Width,
alpha,
10 );
break;
case ATS_8S:
atsbInitEllipse( (uchar*)src->imageData,
roi.width,
roi.height,
src->widthStep,
x,
y,
Length,
Width,
alpha,
10 );
break;
case ATS_32F:
atsfInitEllipse( (float*)src->imageData,
roi.width,
roi.height,
src->widthStep,
x,
y,
Length,
Width,
alpha,
10 );
break;
} /* switch( Flvr ) */
putchar('.');
for( i = 0; i < steps; i++ )
{
CvConnectedComp comp;
CvBox2D box;
destIters = cvCamShift( src, Window, criteria, &comp, &box );
Window = comp.rect;
destArea = (float) comp.area;
destOrientation = box.angle;
destLen = box.size.height;
destWidth = box.size.width;
}
/* Checking results */
/* Checking orientation */
if( fabs( alpha - destOrientation ) > 0.01 &&
fabs( alpha + Pi - destOrientation ) > 0.01 )
{
Errors++;
trsWrite( ATS_LST,
"orientation: act: %f, exp: %f\n",
destOrientation,
alpha );
}
/* Checking length */
if( fabs( destLen - Length * 2 ) > epsilon )
{
Errors++;
trsWrite( ATS_LST,
"length: act: %f, exp: %d\n",
destLen,
Length );
}
/* Checking width */
if( fabs( destWidth - Width * 2 ) > epsilon )
{
Errors++;
trsWrite( ATS_LST,
"width: act: %f, exp: %d\n",
destWidth,
Width );
}
}
cvReleaseImage(&src);
return Errors == 0 ? TRS_OK : trsResult( TRS_FAIL, "Fixed %d errors", Errors );
} /* foaCamShiftC1R */
int main222( int argc, char** argv )
{
CvCapture* capture = 0;
if( argc == 1 || (argc == 2 && strlen(argv[1]) == 1 && isdigit(argv[1][0])))
capture = cvCaptureFromCAM( argc == 2 ? argv[1][0] - '0' : 0 );
else if( argc == 2 )
capture = cvCaptureFromAVI( argv[1] );
if( !capture )
{
fprintf(stderr,"Could not initialize capturing...\n");
return -1;
}
printf( "Hot keys: \n"
"\tESC - quit the program\n"
"\tc - stop the tracking\n"
"\tb - switch to/from backprojection view\n"
"\th - show/hide object histogram\n"
"To initialize tracking, select the object with mouse\n" );
cvNamedWindow( "Histogram", 1 );
cvNamedWindow( "CamShiftDemo", 1 );
cvSetMouseCallback( "CamShiftDemo", on_mouse, 0 );
cvCreateTrackbar( "Vmin", "CamShiftDemo", &vmin, 256, 0 );
cvCreateTrackbar( "Vmax", "CamShiftDemo", &vmax, 256, 0 );
cvCreateTrackbar( "Smin", "CamShiftDemo", &smin, 256, 0 );
for(;;)
{
IplImage* frame = 0;
int i, bin_w, c;
if( !frame )
break;
if( !image )
{
/* allocate all the buffers */
image = cvCreateImage( cvGetSize(frame), 8, 3 );
image->origin = frame->origin;
hsv = cvCreateImage( cvGetSize(frame), 8, 3 );
hue = cvCreateImage( cvGetSize(frame), 8, 1 );
mask = cvCreateImage( cvGetSize(frame), 8, 1 );
backproject = cvCreateImage( cvGetSize(frame), 8, 1 );
hist = cvCreateHist( 1, &hdims, CV_HIST_ARRAY, &hranges, 1 );
histimg = cvCreateImage( cvSize(320,200), 8, 3 );
cvZero( histimg );
}
cvCopy( frame, image, 0 );
cvCvtColor( image, hsv, CV_BGR2HSV );
if( track_object )
{
int _vmin = vmin, _vmax = vmax;
cvInRangeS( hsv, cvScalar(0,smin,MIN(_vmin,_vmax),0),
cvScalar(180,256,MAX(_vmin,_vmax),0), mask );
cvSplit( hsv, hue, 0, 0, 0 );
if( track_object < 0 )
{
float max_val = 0.f;
cvSetImageROI( hue, selection );
cvSetImageROI( mask, selection );
cvCalcHist( &hue, hist, 0, mask );
cvGetMinMaxHistValue( hist, 0, &max_val, 0, 0 );
cvConvertScale( hist->bins, hist->bins, max_val ? 255. / max_val : 0., 0 );
cvResetImageROI( hue );
cvResetImageROI( mask );
track_window = selection;
track_object = 1;
cvZero( histimg );
bin_w = histimg->width / hdims;
for( i = 0; i < hdims; i++ )
{
int val = cvRound( cvGetReal1D(hist->bins,i)*histimg->height/255 );
CvScalar color = hsv2rgb(i*180.f/hdims);
cvRectangle( histimg, cvPoint(i*bin_w,histimg->height),
cvPoint((i+1)*bin_w,histimg->height - val),
color, -1, 8, 0 );
}
}
cvCalcBackProject( &hue, backproject, hist );
cvAnd( backproject, mask, backproject, 0 );
cvCamShift( backproject, track_window,
cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),
&track_comp, &track_box );
track_window = track_comp.rect;
if( backproject_mode )
cvCvtColor( backproject, image, CV_GRAY2BGR );
if( !image->origin )
track_box.angle = -track_box.angle;
cvEllipseBox( image, track_box, CV_RGB(255,0,0), 3, CV_AA, 0 );
}
if( select_object && selection.width > 0 && selection.height > 0 )
{
cvSetImageROI( image, selection );
cvXorS( image, cvScalarAll(255), image, 0 );
cvResetImageROI( image );
}
cvShowImage( "CamShiftDemo", image );
cvShowImage( "Histogram", histimg );
c = cvWaitKey(10);
if( (char) c == 27 )
break;
switch( (char) c )
{
case 'b':
backproject_mode ^= 1;
break;
case 'c':
track_object = 0;
cvZero( histimg );
break;
case 'h':
show_hist ^= 1;
if( !show_hist )
cvDestroyWindow( "Histogram" );
else
cvNamedWindow( "Histogram", 1 );
break;
default:
;
}
}
cvReleaseCapture( &capture );
cvDestroyWindow("CamShiftDemo");
return 0;
}
int track( IplImage* frame, int flag,int Cx,int Cy,int R )
{
{
int i, bin_w, c;
LOGE("#######################Check1############################");
if( !image )
{
/* allocate all the buffers */
image = cvCreateImage( cvGetSize(frame), 8, 3 );
image->origin = frame->origin;
hsv = cvCreateImage( cvGetSize(frame), 8, 3 );
hue = cvCreateImage( cvGetSize(frame), 8, 1 );
mask = cvCreateImage( cvGetSize(frame), 8, 1 );
backproject = cvCreateImage( cvGetSize(frame), 8, 1 );
hist = cvCreateHist( 1, &hdims, CV_HIST_ARRAY, &hranges, 1 );
histimg = cvCreateImage( cvSize(320,200), 8, 3 );
cvZero( histimg );
LOGE("######################Check2###########################");
}
cvCopy( frame, image, 0 );
cvCvtColor( image, hsv, CV_BGR2HSV );
{
int _vmin = vmin, _vmax = vmax;
cvInRangeS( hsv, cvScalar(0,smin,MIN(_vmin,_vmax),0),
cvScalar(180,256,MAX(_vmin,_vmax),0), mask );
cvSplit( hsv, hue, 0, 0, 0 );
LOGE("###########################Check3######################");
if(flag==0)
{
LOGE("###############Initialized#############################");
selection.x=Cx-R;
selection.y=Cy-R;
selection.height=2*R;
selection.width=2*R;
float max_val = 0.f;
cvSetImageROI( hue, selection );
cvSetImageROI( mask, selection );
cvCalcHist( &hue, hist, 0, mask );
cvGetMinMaxHistValue( hist, 0, &max_val, 0, 0 );
cvConvertScale( hist->bins, hist->bins, max_val ? 255. / max_val : 0., 0 );
cvResetImageROI( hue );
cvResetImageROI( mask );
track_window = selection;
track_object = 1;
cvZero( histimg );
bin_w = histimg->width / hdims;
for( i = 0; i < hdims; i++ )
{
int val = cvRound( cvGetReal1D(hist->bins,i)*histimg->height/255 );
CvScalar color = hsv2rgb(i*180.f/hdims);
cvRectangle( histimg, cvPoint(i*bin_w,histimg->height),
cvPoint((i+1)*bin_w,histimg->height - val),
color, -1, 8, 0 );
}
LOGE("##############Check4#########################");
}
LOGE("##############Check5#########################");
cvCalcBackProject( &hue, backproject, hist );
cvAnd( backproject, mask, backproject, 0 );
cvCamShift( backproject, track_window,
cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ),
&track_comp, &track_box );
track_window = track_comp.rect;
char buffer[50];
sprintf(buffer,"vals= %d %d and %d",track_window.x,track_window.y,track_window.width);
LOGE(buffer);
if( backproject_mode )
cvCvtColor( backproject, image, CV_GRAY2BGR );
if( image->origin )
track_box.angle = -track_box.angle;
cvEllipseBox( image, track_box, CV_RGB(255,0,0), 3, CV_AA, 0 );
}
if( select_object && selection.width > 0 && selection.height > 0 )
{
cvSetImageROI( image, selection );
cvXorS( image, cvScalarAll(255), image, 0 );
cvResetImageROI( image );
}
LOGE("!!!!!!!!!!!!!!!!!!Done Tracking!!!!!!!!!!!!!!!!!!!!!!!!!!!!");
}
return 0;
}
