bool Tracker::initFace(TrackerParams* params, Matrixu &frame)
{
const char* cascade_name = "haarcascade_frontalface_alt_tree.xml";
const int minsz = 20;
if( Tracker::facecascade == NULL )
Tracker::facecascade = (CvHaarClassifierCascade*)cvLoad( cascade_name, 0, 0, 0 );
frame.createIpl();
IplImage *img = frame.getIpl();
IplImage* gray = cvCreateImage( cvSize(img->width, img->height), IPL_DEPTH_8U, 1 );
cvCvtColor(img, gray, CV_BGR2GRAY );
frame.freeIpl();
cvEqualizeHist(gray, gray);
CvMemStorage* storage = cvCreateMemStorage(0);
cvClearMemStorage(storage);
CvSeq* faces = cvHaarDetectObjects(gray, Tracker::facecascade, storage, 1.05, 3, CV_HAAR_DO_CANNY_PRUNING ,cvSize(minsz, minsz));
int index = faces->total-1;
CvRect* r = (CvRect*)cvGetSeqElem( faces, index );
while(r && (r->width<minsz || r->height<minsz || (r->y+r->height+10)>frame.rows() || (r->x+r->width)>frame.cols() ||
r->y<0 || r->x<0)){
r = (CvRect*)cvGetSeqElem( faces, --index);
}
//if( r == NULL ){
// cout << "ERROR: no face" << endl;
// return false;
//}
//else
// cout << "Face Found: " << r->x << " " << r->y << " " << r->width << " " << r->height << endl;
if( r==NULL )
return false;
//fprintf(stderr,"x=%f y=%f xmax=%f ymax=%f imgw=%f imgh=%f\n",(float)r->x,(float)r->y,(float)r->x+r->width,(float)r->y+r->height,(float)frame.cols(),(float)frame.rows());
params->_initstate.resize(4);
params->_initstate[0] = (float)r->x;// - r->width;
params->_initstate[1] = (float)r->y;// - r->height;
params->_initstate[2] = (float)r->width;
params->_initstate[3] = (float)r->height+10;
return true;
}
/****************************************************************
Tracker::InitializeWithFace
Initialize the tracker with opencv's face detector.
Exceptions:
None
****************************************************************/
bool Tracker::InitializeWithFace( TrackerParameters* params, Matrixu& frame )
{
const int minsz = 20;
//Get the name of the haar-cascade .xml file
const char* cascade_name = HAAR_CASCADE_FILE_NAME;
ASSERT_TRUE( cascade_name != NULL );
//Load the cascade
if ( Tracker::s_faceCascade == NULL )
{
Tracker::s_faceCascade = (CvHaarClassifierCascade*)cvLoad( cascade_name, 0, 0, 0 );
}
frame.createIpl();
IplImage* img = frame.getIpl();
ASSERT_TRUE( img != NULL );
//convert to grayscale
IplImage* gray = cvCreateImage( cvSize(img->width, img->height), IPL_DEPTH_8U, 1 );
ASSERT_TRUE( gray != NULL );
cvCvtColor(img, gray, CV_BGR2GRAY );
frame.freeIpl();
//histogram equalization
cvEqualizeHist( gray, gray );
//memory storage
CvMemStorage* storage = cvCreateMemStorage(0);
cvClearMemStorage(storage);
//call opencv's haar feature based detector
CvSeq* faces = cvHaarDetectObjects( gray,
Tracker::s_faceCascade,
storage,
1.05,
3,
CV_HAAR_DO_CANNY_PRUNING,
cvSize( minsz, minsz ) );
int index = faces->total-1;
CvRect* r = (CvRect*)cvGetSeqElem( faces, index );
if ( r == NULL )
{
return false;
}
while ( r && (r->width<minsz || r->height < minsz || (r->y+r->height+10)>frame.rows() || (r->x+r->width)>frame.cols() ||
r->y<0 || r->x<0) )
{
r = (CvRect*)cvGetSeqElem( faces, --index );
}
//set the params
params->m_initState.resize(4);
params->m_initState[0] = (float)r->x;
params->m_initState[1] = (float)r->y;
params->m_initState[2] = (float)r->width;
params->m_initState[3] = (float)r->height+10;
return true;
}
