//============================================================================
void ontrackcam(int pos)
{
if(c == 0)
{
c = cvCreateMat(1, g_cam->nModes(), CV_64FC1);cvZero(c);
s = cvCreateMat(1, g_cam->__shape.nPoints()*2, CV_64FC1);
t = cvCreateMat(1, g_cam->__texture.nPixels(), CV_64FC1);
}
double var;
//registrate appearance parameters
for(int i = 0; i < n; i++)
{
var = 3*sqrt(g_cam->Var(i))*(double(b_c[i])/offset-1.0);
cvmSet(c, 0, i, var);
}
//generate shape and texture instance
g_cam->CalcLocalShape(s, c);
g_cam->CalcTexture(t, c);
//warp texture instance from base mesh to current shape instance
aam_s.Mat2Point(s);
int w = aam_s.GetWidth(), h = aam_s.MaxY()-aam_s.MinY();
aam_s.Translate(w, h);
if(image == 0)image = cvCreateImage(cvSize(w*2,h*2), 8, 3);
cvSet(image, cvScalar(128, 128, 128));
g_cam->DrawAppearance(image, aam_s, t);
cvNamedWindow("Combined Appearance Model",1);
cvShowImage("Combined Appearance Model", image);
if(cvWaitKey(10) == '27')
{
cvReleaseImage(&image);
cvReleaseMat(&s);
cvReleaseMat(&t);
cvReleaseMat(&c);
cvDestroyWindow("Parameters");
cvDestroyWindow("Combined Appearance Model");
}
}
//============================================================================
void AAM_IC::Fit(const IplImage* image, AAM_Shape& Shape,
int max_iter /* = 30 */, bool showprocess /* = false */)
{
//initialize some stuff
double t = gettime;
const CvMat* A0 = __texture.GetMean();
CvMat p; cvGetCols(__search_pq, &p, 4, 4+__shape.nModes());
Shape.Point2Mat(__current_s);
SetAllParamsZero();
__shape.CalcParams(__current_s, __search_pq);
IplImage* Drawimg = 0;
for(int iter = 0; iter < max_iter; iter++)
{
if(showprocess)
{
if(Drawimg == 0) Drawimg = cvCloneImage(image);
else cvCopy(image, Drawimg);
Shape.Mat2Point(__current_s);
Draw(Drawimg, Shape, 2);
mkdir("result");
char filename[100];
sprintf(filename, "result/Iter-%02d.jpg", iter);
cvSaveImage(filename, Drawimg);
}
//check the current shape
AAM_Common::CheckShape(__current_s, image->width, image->height);
//warp image to mesh shape mesh
__paw.CalcWarpTexture(__current_s, image, __warp_t);
AAM_TDM::NormalizeTexture(A0, __warp_t);
cvSub(__warp_t, A0, __error_t);
//calculate updates (and scale to account for linear lighting gain)
cvGEMM(__error_t, __G, 1, NULL, 1, __delta_pq, CV_GEMM_B_T);
//check for parameter convergence
if(cvNorm(__delta_pq) < 1e-6) break;
//apply inverse compositional algorithm to update parameters
InverseCompose(__delta_pq, __current_s, __update_s);
//smooth shape
cvAddWeighted(__current_s, 0.4, __update_s, 0.6, 0, __update_s);
//update parameters
__shape.CalcParams(__update_s, __search_pq);
//calculate constrained new shape
__shape.CalcShape(__search_pq, __update_s);
//check for shape convergence
if(cvNorm(__current_s, __update_s, CV_L2) < 0.001) break;
else cvCopy(__update_s, __current_s);
}
Shape.Mat2Point(__current_s);
t = gettime-t;
printf("AAM IC Fitting time cost %.3f millisec\n", t);
cvReleaseImage(&Drawimg);
}
//============================================================================
void AAM_Basic::DrawAppearance(IplImage* image)
{
AAM_Shape Shape; Shape.Mat2Point(__current_s);
AAM_PAW paw;
paw.Train(Shape, __cam.__Points, __cam.__Storage, __cam.__paw.GetTri(), false);
int x1, x2, y1, y2, idx1, idx2;
int tri_idx, v1, v2, v3;
int xby3, idxby3;
int minx, miny, maxx, maxy;
AAM_Shape refShape; refShape.Mat2Point(__cam.__MeanS);
refShape.Translate(-refShape.MinX(), -refShape.MinY());
double minV, maxV;
cvMinMaxLoc(__t_m, &minV, &maxV);
cvConvertScale(__t_m, __t_m, 255/(maxV-minV), -minV*255/(maxV-minV));
byte* pimg;
double* fastt = __t_m->data.db;
minx = Shape.MinX(); miny = Shape.MinY();
maxx = Shape.MaxX(); maxy = Shape.MaxY();
if( minx < 0 )
minx = 0;
else if(minx >= image->width)
minx = image->width - 1;
if( miny < 0 )
miny = 0;
else if(miny >= image->height)
miny = image->height - 1;
if( maxx < 0 )
maxx = 0;
else if(maxx >= image->width)
maxx = image->height - 1;
if( maxy < 0 )
maxy = 0;
else if(maxy >= image->height)
maxy = image->height - 1;
for(int y = miny; y < maxy; y++)
{
y1 = y-miny;
pimg = (byte*)(image->imageData + image->widthStep*y);
for(int x = minx; x < maxx; x++)
{
x1 = x-minx;
idx1 = paw.__rect[y1][x1];
if(idx1 >= 0)
{
tri_idx = paw.PixTri(idx1);
v1 = paw.Tri(tri_idx, 0);
v2 = paw.Tri(tri_idx, 1);
v3 = paw.Tri(tri_idx, 2);
x2 = paw.__alpha[idx1]*refShape[v1].x + paw.__belta[idx1]*refShape[v2].x +
paw.__gamma[idx1]*refShape[v3].x;
y2 = paw.__alpha[idx1]*refShape[v1].y + paw.__belta[idx1]*refShape[v2].y +
paw.__gamma[idx1]*refShape[v3].y;
xby3 = 3*x;
idx2 = __cam.__paw.__rect[y2][x2]; idxby3 = 3*idx2;
pimg[xby3] = fastt[idxby3];
pimg[xby3+1] = fastt[idxby3+1];
pimg[xby3+2] = fastt[idxby3+2];
}
}
}
}
//============================================================================
void AAM_Basic::Fit(const IplImage* image, AAM_Shape& Shape,
int max_iter /* = 30 */,bool showprocess /* = false */)
{
//intial some stuff
double t = gettime;
double e1, e2;
const int np = 5;
double k_values[np] = {1, 0.5, 0.25, 0.125, 0.0625};
int k;
IplImage* Drawimg = 0;
Shape.Point2Mat(__s);
InitParams(image);
CvMat subcq;
cvGetCols(__current_c_q, &subcq, 0, 4); cvCopy(__q, &subcq);
cvGetCols(__current_c_q, &subcq, 4, 4+__cam.nModes()); cvCopy(__c, &subcq);
//calculate error
e1 = EstResidual(image, __current_c_q, __s, __t_m, __t_s, __delta_t);
//do a number of iteration until convergence
for(int iter = 0; iter <max_iter; iter++)
{
if(showprocess)
{
if(Drawimg == 0) Drawimg = cvCloneImage(image);
else cvCopy(image, Drawimg);
__cam.CalcShape(__s, __current_c_q);
Shape.Mat2Point(__s);
Draw(Drawimg, Shape, 2);
#ifdef TARGET_WIN32
mkdir("result");
#else
mkdir("result", S_IRWXU | S_IRWXG | S_IROTH | S_IXOTH);
#endif
char filename[100];
sprintf(filename, "result/ter%d.bmp", iter);
cvSaveImage(filename, Drawimg);
}
// predict parameter update
cvGEMM(__delta_t, __G, 1, NULL, 0, __delta_c_q, CV_GEMM_B_T);
//force first iteration
if(iter == 0)
{
cvAdd(__current_c_q, __delta_c_q, __current_c_q);
CvMat c; cvGetCols(__current_c_q, &c, 4, 4+__cam.nModes());
//constrain parameters
__cam.Clamp(&c);
e1 = EstResidual(image, __current_c_q, __s, __t_m, __t_s, __delta_t);
}
//find largest step size which reduces texture EstResidual
else
{
for(k = 0; k < np; k++)
{
cvScaleAdd(__delta_c_q, cvScalar(k_values[k]), __current_c_q, __update_c_q);
//constrain parameters
CvMat c; cvGetCols(__update_c_q, &c, 4, 4+__cam.nModes());
__cam.Clamp(&c);
e2 = EstResidual(image, __update_c_q, __s, __t_m, __t_s, __delta_t);
if(e2 <= e1) break;
}
}
//check for convergence
if(iter > 0)
{
if(k == np)
{
e1 = e2;
cvCopy(__update_c_q, __current_c_q);
}
else if(fabs(e2-e1)<0.001*e1) break;
else if (cvNorm(__delta_c_q)<0.001) break;
else
{
cvCopy(__update_c_q, __current_c_q);
e1 = e2;
}
}
}
cvReleaseImage(&Drawimg);
__cam.CalcShape(__s, __current_c_q);
Shape.Mat2Point(__s);
t = gettime - t;
printf("AAM-Basic Fitting time cost: %.3f millisec\n", t);
}
//============================================================================
int AAM_Basic::Fit(const IplImage* image, AAM_Shape& Shape,
int max_iter /* = 30 */,bool showprocess /* = false */)
{
//intial some stuff
double t = curtime;
double e1, e2, e3;
double k_v[6] = {-1,-1.15,-0.7,-0.5,-0.2,-0.0625};
Shape.Point2Mat(__current_s);
InitParams(image, __current_s, __current_c);
__cam.__shape.CalcParams(__current_s, __p, __current_q);
cvZero(__current_c);
IplImage* Drawimg =
cvCreateImage(cvGetSize(image), image->depth, image->nChannels);
//mkdir("result");
//char filename[100];
//calculate error
e3 = EstResidual(image, __current_c, __current_s, __delta_t);
if(e3 == -1) return 0;
int iter;
//do a number of iteration until convergence
for( iter = 0; iter <max_iter; iter++)
{
// predict pose and parameter update
// __delta_t rosszul számolódik. Kiiratás ld. AAM_Sahpe::Mat2Point()
//cvGEMM(__delta_t, __Rq, 1, NULL, 0, __delta_q, CV_GEMM_B_T);
cvGEMM(__delta_t, __Rc, 1, NULL, 0, __delta_c, CV_GEMM_B_T);
// if the prediction above didn't improve th fit,
// try amplify and later damp the prediction
for(int k = 0; k < 6; k++)
{
cvScaleAdd(__delta_q, cvScalar(k_v[k]), __current_q, __update_q);
cvScaleAdd(__delta_c, cvScalar(k_v[k]), __current_c, __update_c);
__cam.Clamp(__update_c);//constrain parameters
e2 = EstResidual(image, __update_c, __current_s, __delta_t);
if(k==0) e1 = e2;
else if(e2 != -1 && e2 < e1)break;
}
//check for convergence
if((iter>max_iter/3&&fabs(e2-e3)<0.01*e3) || e2<0.001 )
{
break;
}
else if (cvNorm(__delta_c)<0.001 && cvNorm(__delta_q)<0.001)
{
break;
}
else
{
cvCopy(__update_q, __current_q);
cvCopy(__update_c, __current_c);
e3 = e2;
}
}
__cam.CalcShape(__current_s, __current_c, __current_q);
Shape.Mat2Point(__current_s);
t = curtime - t;
if( AAM_DEBUG_MODE ) printf("AAM-Basic Fitting time cost: %.3f\n", t);
return iter;
}
