void sum_rgb( IplImage* src, IplImage* dst ) {
// Allocate individual image planes.
IplImage* r = cvCreateImage( cvGetSize(src), IPL_DEPTH_8U, 1 );
IplImage* g = cvCreateImage( cvGetSize(src), IPL_DEPTH_8U, 1 );
IplImage* b = cvCreateImage( cvGetSize(src), IPL_DEPTH_8U, 1 );
// Temporary storage.
IplImage* s = cvCreateImage(cvGetSize(src), IPL_DEPTH_32F, 1);
// Split image onto the color planes.
cvSplit( src, r, g, b, NULL );
// Accumulate separate planes, combine and threshold.
cvZero(s);
cvAcc(b,s);
cvAcc(g,s);
cvAcc(r,s);
// Truncate values above 100 and rescale into dst.
cvThreshold( s, s, 100, 100, CV_THRESH_TRUNC );
cvConvertScale( s, dst, 1, 0 );
cvReleaseImage( &r );
cvReleaseImage( &g );
cvReleaseImage( &b );
cvReleaseImage( &s );
}
// Learn the background statistics for one more frame
void accumulateBackground( IplImage *I ){
static int first = 1;
cvCvtScale( I, Iscratch, 1, 0 );
if( !first ){
cvAcc( Iscratch, IavgF );
cvAbsDiff( Iscratch, IprevF, Iscratch2 );
cvAcc( Iscratch2, IdiffF );
Icount += 1.0;
}
first = 0;
cvCopy( Iscratch, IprevF );
}
// Accumulate the background statistics for one more frame
// We accumulate the images, the image differences and the count of images for the
// the routine createModelsfromStats() to work on after we're done accumulating N frames.
// I Background image, 3 channel, 8u
// number Camera number
void accumulateBackground(IplImage *I, int number)
{
static int first = 1;
cvCvtScale(I,Iscratch,1,0); //To float;
if (!first){
cvAcc(Iscratch,IavgF[number]);
cvAbsDiff(Iscratch,IprevF[number],Iscratch2);
cvAcc(Iscratch2,IdiffF[number]);
Icount[number] += 1.0;
}
first = 0;
cvCopy(Iscratch,IprevF[number]);
}
// --------------------------------------------------------------------------
void BlobModel::UpdateHeatMap(IplImage* motionmap) {
// for each head candidate draw a circle on the floor; add it to the heatmap image
// NOTE: due to scaling, circle becomes an ellipse
double BLOB_RADIUS = 50; // blob projection on the floor average radius in centimeters
bool oneclose = false;
for (int i=0;i<blob.GetCount();i++) {
CvSeq* heads = doc->blobmodel.blob[i]->heads;
for (int j=0;j<heads->total;j++) {
BlobRay* br = (BlobRay*)cvGetSeqElem(heads, j);
CvPoint3D32f head, foot;
doc->cameramodel.coordsImage2RealSameXY_Feet2Floor(cvPointTo32f(br->p1), cvPointTo32f(br->p2), &head, &foot);
// ignore short candidates
if (head.z < doc->bodymodel.m_minHeight)
continue;
// ignore repeating artifact closeby candidates
if (oneclose)
continue;
if (d(foot) < BLOB_RADIUS*2)
oneclose = true;
CvPoint c = doc->floormodel.coordsReal2Floor(foot);
CvSize axes = doc->floormodel.sizeReal2Floor(cvSize2D32f(BLOB_RADIUS, BLOB_RADIUS));
cvZero(motionmaptemp);
cvEllipse(motionmaptemp, c, axes, 0, 0, 360, cvScalar(1), CV_FILLED);
cvAcc(motionmaptemp, motionmap);
}
}
}
bool MT_BackgroundFrameCreator::DoStep()
{
if(m_iStatus == MT_MAKEBG_ERR)
{
return false;
}
IplImage* Frame; // this memory is managed by the capture object
if(m_pCapture->getMode() == MT_FC_MODE_AVI)
{
// generate a random frame index
double frame_index = floor(MT_frandr(m_iStartFrame, m_iEndFrame));
// get the frame
Frame = m_pCapture->getFrame(frame_index);
if(m_bDoInpaint)
{
do_inpainting(Frame, m_iInpaintRadius, m_InpaintROI);
}
// accumulate this frame into the BG frame (divide at end)
cvAcc(Frame, m_pBG);
}
if(m_pCapture->getMode() == MT_FC_MODE_CAM)
{
/* for now all we'll do is get consecutive frames */
Frame = m_pCapture->getFrame();
if(m_bDoInpaint)
{
do_inpainting(Frame, m_iInpaintRadius, m_InpaintROI);
}
// accumulate this frame into the BG frame (divide at end)
cvAcc(Frame, m_pBG);
}
return true;
}
// Accumulate the background statistics for one more frame.
// We accumulate the images, the image differences and the count of images for the
// the routine createModelsfromStats() to work on after we're done accumulating N frames.
//
// Parameters:
// I: Background image, 3 channel, 8u
// number: Camera number
void accumulateBackground(IplImage *I, int number)
{
static int first = 1; // nb. Not thread safe
// Turn the raw background 8-bit-per-channel, three-color-channel image into a
// floating-point three-channel image.
cvCvtScale(I, Iscratch, 1, 0);
if (!first)
{
// Learn the accumulated background image.
cvAcc(Iscratch, IavgF[number]);
// Learn the accumulated absolute value of frame-to-frame image differences.
cvAbsDiff(Iscratch, IprevF[number], Iscratch2);
cvAcc(Iscratch2, IdiffF[number]);
Icount[number] += 1.0;
}
first = 0;
cvCopy(Iscratch, IprevF[number]);
}
void
icvCrossCorr( const CvArr* _img, const CvArr* _templ, CvArr* _corr,
CvPoint anchor, double delta, int borderType )
{
// disable OpenMP in the case of Visual Studio,
// otherwise the performance drops significantly
#undef USE_OPENMP
#if !defined _MSC_VER || defined CV_ICC
#define USE_OPENMP 1
#endif
const double block_scale = 4.5;
const int min_block_size = 256;
cv::Ptr<CvMat> dft_img[CV_MAX_THREADS];
cv::Ptr<CvMat> dft_templ;
std::vector<uchar> buf[CV_MAX_THREADS];
int k, num_threads = 0;
CvMat istub, *img = (CvMat*)_img;
CvMat tstub, *templ = (CvMat*)_templ;
CvMat cstub, *corr = (CvMat*)_corr;
CvSize dftsize, blocksize;
int depth, templ_depth, corr_depth, max_depth = CV_32F,
cn, templ_cn, corr_cn, buf_size = 0,
tile_count_x, tile_count_y, tile_count;
img = cvGetMat( img, &istub );
templ = cvGetMat( templ, &tstub );
corr = cvGetMat( corr, &cstub );
if( CV_MAT_DEPTH( img->type ) != CV_8U &&
CV_MAT_DEPTH( img->type ) != CV_16U &&
CV_MAT_DEPTH( img->type ) != CV_32F &&
CV_MAT_DEPTH( img->type ) != CV_64F )
CV_Error( CV_StsUnsupportedFormat,
"The function supports only 8u, 16u and 32f data types" );
if( !CV_ARE_DEPTHS_EQ( img, templ ) && CV_MAT_DEPTH( templ->type ) != CV_32F )
CV_Error( CV_StsUnsupportedFormat,
"Template (kernel) must be of the same depth as the input image, or be 32f" );
if( !CV_ARE_DEPTHS_EQ( img, corr ) && CV_MAT_DEPTH( corr->type ) != CV_32F &&
CV_MAT_DEPTH( corr->type ) != CV_64F )
CV_Error( CV_StsUnsupportedFormat,
"The output image must have the same depth as the input image, or be 32f/64f" );
if( (!CV_ARE_CNS_EQ( img, corr ) || CV_MAT_CN(templ->type) > 1) &&
(CV_MAT_CN( corr->type ) > 1 || !CV_ARE_CNS_EQ( img, templ)) )
CV_Error( CV_StsUnsupportedFormat,
"The output must have the same number of channels as the input (when the template has 1 channel), "
"or the output must have 1 channel when the input and the template have the same number of channels" );
depth = CV_MAT_DEPTH(img->type);
cn = CV_MAT_CN(img->type);
templ_depth = CV_MAT_DEPTH(templ->type);
templ_cn = CV_MAT_CN(templ->type);
corr_depth = CV_MAT_DEPTH(corr->type);
corr_cn = CV_MAT_CN(corr->type);
CV_Assert( corr_cn == 1 || delta == 0 );
max_depth = MAX( max_depth, templ_depth );
max_depth = MAX( max_depth, depth );
max_depth = MAX( max_depth, corr_depth );
if( depth > CV_8U )
max_depth = CV_64F;
/*if( img->cols < templ->cols || img->rows < templ->rows )
CV_Error( CV_StsUnmatchedSizes,
"Such a combination of image and template/filter size is not supported" );*/
if( corr->rows > img->rows + templ->rows - 1 ||
corr->cols > img->cols + templ->cols - 1 )
CV_Error( CV_StsUnmatchedSizes,
"output image should not be greater than (W + w - 1)x(H + h - 1)" );
blocksize.width = cvRound(templ->cols*block_scale);
blocksize.width = MAX( blocksize.width, min_block_size - templ->cols + 1 );
blocksize.width = MIN( blocksize.width, corr->cols );
blocksize.height = cvRound(templ->rows*block_scale);
blocksize.height = MAX( blocksize.height, min_block_size - templ->rows + 1 );
blocksize.height = MIN( blocksize.height, corr->rows );
dftsize.width = cvGetOptimalDFTSize(blocksize.width + templ->cols - 1);
if( dftsize.width == 1 )
dftsize.width = 2;
dftsize.height = cvGetOptimalDFTSize(blocksize.height + templ->rows - 1);
if( dftsize.width <= 0 || dftsize.height <= 0 )
CV_Error( CV_StsOutOfRange, "the input arrays are too big" );
// recompute block size
blocksize.width = dftsize.width - templ->cols + 1;
blocksize.width = MIN( blocksize.width, corr->cols );
blocksize.height = dftsize.height - templ->rows + 1;
blocksize.height = MIN( blocksize.height, corr->rows );
dft_templ = cvCreateMat( dftsize.height*templ_cn, dftsize.width, max_depth );
#ifdef USE_OPENMP
num_threads = cvGetNumThreads();
#else
num_threads = 1;
#endif
for( k = 0; k < num_threads; k++ )
dft_img[k] = cvCreateMat( dftsize.height, dftsize.width, max_depth );
if( templ_cn > 1 && templ_depth != max_depth )
buf_size = templ->cols*templ->rows*CV_ELEM_SIZE(templ_depth);
if( cn > 1 && depth != max_depth )
buf_size = MAX( buf_size, (blocksize.width + templ->cols - 1)*
(blocksize.height + templ->rows - 1)*CV_ELEM_SIZE(depth));
if( (corr_cn > 1 || cn > 1) && corr_depth != max_depth )
buf_size = MAX( buf_size, blocksize.width*blocksize.height*CV_ELEM_SIZE(corr_depth));
if( buf_size > 0 )
{
for( k = 0; k < num_threads; k++ )
buf[k].resize(buf_size);
}
// compute DFT of each template plane
for( k = 0; k < templ_cn; k++ )
{
CvMat dstub, *src, *dst, temp;
CvMat* planes[] = { 0, 0, 0, 0 };
int yofs = k*dftsize.height;
src = templ;
dst = cvGetSubRect( dft_templ, &dstub, cvRect(0,yofs,templ->cols,templ->rows));
if( templ_cn > 1 )
{
planes[k] = templ_depth == max_depth ? dst :
cvInitMatHeader( &temp, templ->rows, templ->cols, templ_depth, &buf[0][0] );
cvSplit( templ, planes[0], planes[1], planes[2], planes[3] );
src = planes[k];
planes[k] = 0;
}
if( dst != src )
cvConvert( src, dst );
if( dft_templ->cols > templ->cols )
{
cvGetSubRect( dft_templ, dst, cvRect(templ->cols, yofs,
dft_templ->cols - templ->cols, templ->rows) );
cvZero( dst );
}
cvGetSubRect( dft_templ, dst, cvRect(0,yofs,dftsize.width,dftsize.height) );
cvDFT( dst, dst, CV_DXT_FORWARD + CV_DXT_SCALE, templ->rows );
}
tile_count_x = (corr->cols + blocksize.width - 1)/blocksize.width;
tile_count_y = (corr->rows + blocksize.height - 1)/blocksize.height;
tile_count = tile_count_x*tile_count_y;
#if defined _OPENMP && defined USE_OPENMP
#pragma omp parallel for num_threads(num_threads) schedule(dynamic)
#endif
// calculate correlation by blocks
for( k = 0; k < tile_count; k++ )
{
#ifdef USE_OPENMP
int thread_idx = cvGetThreadNum();
#else
int thread_idx = 0;
#endif
int x = (k%tile_count_x)*blocksize.width;
int y = (k/tile_count_x)*blocksize.height;
int i, yofs;
CvMat sstub, dstub, *src, *dst, temp;
CvMat* planes[] = { 0, 0, 0, 0 };
CvMat* _dft_img = dft_img[thread_idx];
uchar* _buf = buf_size > 0 ? &buf[thread_idx][0] : 0;
CvSize csz = { blocksize.width, blocksize.height }, isz;
int x0 = x - anchor.x, y0 = y - anchor.y;
int x1 = MAX( 0, x0 ), y1 = MAX( 0, y0 ), x2, y2;
csz.width = MIN( csz.width, corr->cols - x );
csz.height = MIN( csz.height, corr->rows - y );
isz.width = csz.width + templ->cols - 1;
isz.height = csz.height + templ->rows - 1;
x2 = MIN( img->cols, x0 + isz.width );
y2 = MIN( img->rows, y0 + isz.height );
for( i = 0; i < cn; i++ )
{
CvMat dstub1, *dst1;
yofs = i*dftsize.height;
src = cvGetSubRect( img, &sstub, cvRect(x1,y1,x2-x1,y2-y1) );
dst = cvGetSubRect( _dft_img, &dstub,
cvRect(0,0,isz.width,isz.height) );
dst1 = dst;
if( x2 - x1 < isz.width || y2 - y1 < isz.height )
dst1 = cvGetSubRect( _dft_img, &dstub1,
cvRect( x1 - x0, y1 - y0, x2 - x1, y2 - y1 ));
if( cn > 1 )
{
planes[i] = dst1;
if( depth != max_depth )
planes[i] = cvInitMatHeader( &temp, y2 - y1, x2 - x1, depth, _buf );
cvSplit( src, planes[0], planes[1], planes[2], planes[3] );
src = planes[i];
planes[i] = 0;
}
if( dst1 != src )
cvConvert( src, dst1 );
if( dst != dst1 )
cvCopyMakeBorder( dst1, dst, cvPoint(x1 - x0, y1 - y0), borderType );
if( dftsize.width > isz.width )
{
cvGetSubRect( _dft_img, dst, cvRect(isz.width, 0,
dftsize.width - isz.width,dftsize.height) );
cvZero( dst );
}
cvDFT( _dft_img, _dft_img, CV_DXT_FORWARD, isz.height );
cvGetSubRect( dft_templ, dst,
cvRect(0,(templ_cn>1?yofs:0),dftsize.width,dftsize.height) );
cvMulSpectrums( _dft_img, dst, _dft_img, CV_DXT_MUL_CONJ );
cvDFT( _dft_img, _dft_img, CV_DXT_INVERSE, csz.height );
src = cvGetSubRect( _dft_img, &sstub, cvRect(0,0,csz.width,csz.height) );
dst = cvGetSubRect( corr, &dstub, cvRect(x,y,csz.width,csz.height) );
if( corr_cn > 1 )
{
planes[i] = src;
if( corr_depth != max_depth )
{
planes[i] = cvInitMatHeader( &temp, csz.height, csz.width,
corr_depth, _buf );
cvConvertScale( src, planes[i], 1, delta );
}
cvMerge( planes[0], planes[1], planes[2], planes[3], dst );
planes[i] = 0;
}
else
{
if( i == 0 )
cvConvertScale( src, dst, 1, delta );
else
{
if( max_depth > corr_depth )
{
cvInitMatHeader( &temp, csz.height, csz.width,
corr_depth, _buf );
cvConvert( src, &temp );
src = &temp;
}
cvAcc( src, dst );
}
}
}
}
}
/*
Generate a calibration image based on the average of some
accumulated images.
*/
int generate_cal_image (const char *dir, int num_cal_images)
{
int key, i;
CvScalar bkgd_color, one;
IplImage *img, *cal_img, *sum_img, *mask;
CvSize size = { IMAGE_WIDTH, IMAGE_HEIGHT };
img = cvCreateImage(size, IPL_DEPTH_8U, 1);
if (!img)
return 0;
cal_img = cvCreateImage(size, IPL_DEPTH_8U, 1);
if (!cal_img) {
cvReleaseImage(&img);
return 0;
}
mask = cvCreateImage(size, IPL_DEPTH_8U, 1);
if (!mask) {
cvReleaseImage(&img);
cvReleaseImage(&cal_img);
return 0;
}
sum_img = cvCreateImage(size, IPL_DEPTH_32F, 1);
if (!sum_img) {
cvReleaseImage(&img);
cvReleaseImage(&cal_img);
cvReleaseImage(&mask);
return 0;
}
bkgd_color.val[0] = BACKGROUND_COLOR;
cvSet(img, bkgd_color, NULL);
cvSet(cal_img, bkgd_color, NULL);
one.val[0] = 1.0;
cvSet(mask, one, NULL);
cvZero(sum_img);
for (i = 0; i < num_cal_images; i++) {
draw_shapes(img);
save_image(dir, img, i);
cvAcc(img, sum_img, mask);
cvZero(cal_img);
cvConvertScale(sum_img, cal_img, 1.0 / (i + 1), 0);
cvShowImage("shapegen", cal_img);
if (dir)
key = 0xff & cvWaitKey(500);
else
key = 0xff & cvWaitKey(0);
if (key == ESCAPE_KEY)
break;
}
if (key != ESCAPE_KEY)
save_image(dir, cal_img, -1);
cvReleaseImage(&img);
cvReleaseImage(&cal_img);
cvReleaseImage(&sum_img);
cvReleaseImage(&mask);
return (key != ESCAPE_KEY);
}
int main(int argc, char **argv)
{
bool isStop = false;
const int INIT_TIME = 50;
const double BG_RATIO = 0.02; // 背景領域更新レート
const double OBJ_RATIO = 0.005; // 物体領域更新レート
const double Zeta = 10.0;
IplImage *img = NULL;
CvCapture *capture = NULL;
capture = cvCreateCameraCapture(0);
//capture = cvCaptureFromAVI("test.avi");
if(capture == NULL){
printf("capture device not found!!");
return -1;
}
img = cvQueryFrame(capture);
int w = img->width;
int h = img->height;
IplImage *imgAverage = cvCreateImage(cvSize(w, h), IPL_DEPTH_32F, 3);
IplImage *imgSgm = cvCreateImage(cvSize(w, h), IPL_DEPTH_32F, 3);
IplImage *imgTmp = cvCreateImage(cvSize(w, h), IPL_DEPTH_32F, 3);
IplImage *img_lower = cvCreateImage(cvSize(w, h), IPL_DEPTH_32F, 3);
IplImage *img_upper = cvCreateImage(cvSize(w, h), IPL_DEPTH_32F, 3);
IplImage *imgSilhouette = cvCreateImage(cvSize(w, h), IPL_DEPTH_8U, 1);
IplImage *imgSilhouetteInv = cvCreateImage(cvSize(w, h), IPL_DEPTH_8U, 1);
IplImage *imgResult = cvCreateImage(cvSize(w, h), IPL_DEPTH_8U, 3);
printf("背景初期化中...\n");
cvSetZero(imgAverage);
for(int i = 0; i < INIT_TIME; i++){
img = cvQueryFrame(capture);
cvAcc(img, imgAverage);
printf("輝度平均 %d/%d\n", i, INIT_TIME);
}
cvConvertScale(imgAverage, imgAverage, 1.0 / INIT_TIME);
cvSetZero(imgSgm);
for(int i = 0; i < INIT_TIME; i++){
img = cvQueryFrame(capture);
cvConvert(img, imgTmp);
cvSub(imgTmp, imgAverage, imgTmp);
cvPow(imgTmp, imgTmp, 2.0);
cvConvertScale(imgTmp, imgTmp, 2.0);
cvPow(imgTmp, imgTmp, 0.5);
cvAcc(imgTmp, imgSgm);
printf("輝度振幅 %d/%d\n", i, INIT_TIME);
}
cvConvertScale(imgSgm, imgSgm, 1.0 / INIT_TIME);
printf("背景初期化完了\n");
char winNameCapture[] = "Capture";
char winNameSilhouette[] = "Silhouette";
cvNamedWindow(winNameCapture, CV_WINDOW_AUTOSIZE);
cvNamedWindow(winNameSilhouette, CV_WINDOW_AUTOSIZE);
while(1){
if(!isStop){
img = cvQueryFrame(capture);
if(img == NULL) break;
cvConvert(img, imgTmp);
// 輝度範囲
cvSub(imgAverage, imgSgm, img_lower);
cvSubS(img_lower, cvScalarAll(Zeta), img_lower);
cvAdd(imgAverage, imgSgm, img_upper);
cvAddS(img_upper, cvScalarAll(Zeta), img_upper);
cvInRange(imgTmp, img_lower, img_upper, imgSilhouette);
// 輝度振幅
cvSub(imgTmp, imgAverage, imgTmp);
cvPow(imgTmp, imgTmp, 2.0);
cvConvertScale(imgTmp, imgTmp, 2.0);
cvPow(imgTmp, imgTmp, 0.5);
// 背景領域を更新
cvRunningAvg(img, imgAverage, BG_RATIO, imgSilhouette);
cvRunningAvg(imgTmp, imgSgm, BG_RATIO, imgSilhouette);
// 物体領域を更新
cvNot(imgSilhouette, imgSilhouetteInv);
cvRunningAvg(imgTmp, imgSgm, OBJ_RATIO, imgSilhouetteInv);
cvErode(imgSilhouette, imgSilhouette, NULL, 1); // 収縮
cvDilate(imgSilhouette, imgSilhouette, NULL, 2); // 膨張
cvErode(imgSilhouette, imgSilhouette, NULL, 1); // 収縮
cvMerge(imgSilhouette, imgSilhouette, imgSilhouette, NULL, imgResult);
cvShowImage(winNameCapture, img);
cvShowImage(winNameSilhouette, imgResult);
}
int waitKey = cvWaitKey(33);
if(waitKey == 'q') break;
if(waitKey == ' '){
isStop = !isStop;
if(isStop) printf("stop\n");
else printf("start\n");
}
}
cvReleaseCapture(&capture);
cvDestroyWindow(winNameCapture);
cvDestroyWindow(winNameSilhouette);
return 0;
}
