void BazARTracker::update()
{
// Do not update with a null image
if (m_imageptr == NULL) return;
// Image format conversion for BAZAR
for(int i=0; i<m_cparam->cparam.xsize*m_cparam->cparam.ysize*4; i++)
{
image->imageData[i] = m_imageptr[i];
}
// Image format change for processing color->gray
if(image->nChannels == 4)
{
cvCvtColor(image, gray, CV_RGBA2GRAY);
}
else if(image->nChannels == 3)
{
cvCvtColor(image, gray, CV_BGR2GRAY);
}
else
{
gray = image;
}
cvFlip(gray, gray); // bazar uses hoizontially flipped input images
if(getDebugMode()) cvShowImage("Gray", gray); // show what bazar will see
// if the trained planar surface is detected
if (detector.detect(gray))
{
// start on a new frame
augment.Clear();
// we have only 1 camera
add_detected_homography(detector, augment);
// bundle adjust
augment.Accomodate(4, 1e-4);
show_result(augment, image, &display); // GL-projection matrix, if debug: render additional output
if (getDebugMode()) cvShowImage("Result_BAZAR", display);
(static_cast<BazARMarker*>(m_markerlist[0].get()))->update(matCameraRT4_4);
}
else
{
if (getDebugMode()) cvShowImage("Result_BAZAR", display);
(static_cast<BazARMarker*>(m_markerlist[0].get()))->update(NULL);
}
}
bool photometric_calibration(CalibModel &model, CvCapture *capture,
int nbImages, bool cache)
{
if (cache) model.map.load();
const char *win = "BazAR";
IplImage*gray=0;
cvNamedWindow(win, CV_WINDOW_AUTOSIZE);
cvNamedWindow("LightMap", CV_WINDOW_AUTOSIZE);
IplImage* frame = 0;
IplImage* display=cvCloneImage(cvQueryFrame(capture));
int nbHomography =0;
LightCollector lc(model.map.reflc);
IplImage *lightmap = cvCreateImage(cvGetSize(model.map.map.getIm()), IPL_DEPTH_8U,
lc.avgChannels);
while (1)
{
// acquire image
frame = cvQueryFrame( capture );
/*
if (frame) cvReleaseImage(&frame);
frame = cvLoadImage("model.bmp",1);
*/
if( !frame )
break;
// convert it to gray levels, if required
if (frame->nChannels >1) {
if( !gray )
gray = cvCreateImage( cvGetSize(frame), IPL_DEPTH_8U, 1 );
cvCvtColor(frame, gray, CV_RGB2GRAY);
} else {
gray = frame;
}
// run the detector
if (model.detector.detect(gray)) {
// 2d homography found
nbHomography++;
// Computes 3D pose and surface normal
model.augm.Clear();
add_detected_homography(model.detector, model.augm);
model.augm.Accomodate(4, 1e-4);
CvMat *mat = model.augm.GetObjectToWorld();
float normal[3];
for (int j=0;j<3;j++) normal[j] = cvGet2D(mat, j, 2).val[0];
cvReleaseMat(&mat);
// average pixels over triangles
lc.averageImage(frame,model.detector.H);
// add observations
if (!model.map.isReady())
model.map.addNormal(normal, lc, 0);
if (!model.map.isReady() && nbHomography >= nbImages) {
if (model.map.computeLightParams()) {
model.map.save();
const float *gain = model.map.getGain(0);
const float *bias = model.map.getBias(0);
cout << "Gain: " << gain[0] << ", " << gain[1] << ", " << gain[2] << endl;
cout << "Bias: " << bias[0] << ", " << bias[1] << ", " << bias[2] << endl;
}
}
}
if (model.map.isReady()) {
double min, max;
IplImage *map = model.map.map.getIm();
cvSetImageCOI(map, 2);
cvMinMaxLoc(map, &min, &max);
cvSetImageCOI(map, 0);
assert(map->nChannels == lightmap->nChannels);
cvConvertScale(map, lightmap, 128, 0);
cvShowImage("LightMap", lightmap);
augment_scene(model, frame, display);
} else {
cvCopy(frame,display);
if (model.detector.object_is_detected)
lc.drawGrid(display, model.detector.H);
}
cvShowImage(win, display);
int k=cvWaitKey(10);
if (k=='q' || k== 27)
break;
}
cvReleaseImage(&lightmap);
cvReleaseImage(&display);
if (frame->nChannels > 1)
cvReleaseImage(&gray);
return 0;
}
bool geometric_calibration(CalibModel &model, CvCapture *capture, bool cache)
{
if (cache && model.augm.LoadOptimalStructureFromFile("camera_c.txt", "camera_r_t.txt")) {
return true;
}
const char *win = "BazAR";
IplImage*gray=0;
cvNamedWindow(win, CV_WINDOW_AUTOSIZE);
CamCalibration calib;
IplImage* frame = cvQueryFrame(capture);
calib.AddCamera(frame->width, frame->height);
IplImage* display=cvCloneImage(frame);
bool success=false;
int nbHomography =0;
while (1)
{
// acquire image
frame = cvQueryFrame( capture );
if( !frame )
break;
// convert it to gray levels, if required
if (frame->nChannels >1) {
if( !gray )
gray = cvCreateImage( cvGetSize(frame), IPL_DEPTH_8U, 1 );
cvCvtColor(frame, gray, CV_RGB2GRAY);
} else {
gray = frame;
}
// run the detector
if (model.detector.detect(gray)) {
add_detected_homography(model.detector, calib);
nbHomography++;
cout << nbHomography << " homographies.\n";
if (nbHomography >=70) {
if (calib.Calibrate(
50, // max hom
2, // random
3,
3, // padding ratio 1/2
0,
0,
0.0078125, //alpha
0.9, //beta
0.001953125,//gamma
12, // iter
0.05, //eps
3 //postfilter eps
))
{
calib.PrintOptimizedResultsToFile1();
success=true;
break;
}
}
}
show_result(model.detector, frame, display);
cvShowImage(win, display);
int k=cvWaitKey(10);
if (k=='q' || k== 27)
break;
}
cvReleaseImage(&display);
if (frame->nChannels > 1)
cvReleaseImage(&gray);
if (success && model.augm.LoadOptimalStructureFromFile("camera_c.txt", "camera_r_t.txt")) {
return true;
}
return false;
}
