//: Convert a mesh entity to a single point
//: in cartesian coordinates (x,y,z)
void GeomDecomp::entity_to_point (const mesh::Entity & entity,
const VectorField & nodeCoord,
std::vector<double> & coor)
{
compute_entity_centroid(entity, nodeCoord, coor);
apply_rotation (coor);
}
/*
Rotates the tetrimino to the left (counterclockwise)
*/
void rotate_counterclockwise()
{
Tetrimino copy = *in_play;
copy.rotation = (copy.rotation + 3) % 4; //3 is -1 % 4
apply_rotation(copy);
}
/** @brief Extract keypoint feature vector
*
* ----INPUT----
* @param x_key
* @param y_key
* @param sigma_key
* @param theta_key keypoint coordinates.
*
* @param imX
* @param imX precomputed gradient relative to the nearest scale.
*
* ----PARAM----
* @param lambda_descr (=6)
* - The gaussian window has a standard deviation of lambda_descr X=* sigma_key
* - The patch P^descr is ( 2 * lambda_descr * sigma_key * (1+1/Nhist) wide
*
* @param Nhist (=4) number of histograms in each of the two directions,
* @param Nbins (=8) number of bins covering the range [0,2pi]
*
* ----OUTPUT----
* @output descr
*
* ----RETURN----
* @return count number of sample contributing to the descriptor
*/
void sift_extract_feature_vector(float x_key, float y_key, float sigma_key,
float theta_key,
const float* imX, const float* imY,
int w, int h,
int Nhist,
int Nbins,
float lambda_descr,
float* descr)
{
// Initialize descr tab
for(int i = 0; i < Nhist*Nhist*Nbins; i++){descr[i] = 0.0;}
// Contributing pixels are inside a patch [siMin;siMax]X[sjMin;sjMax] of
// width 2*lambda_descr*sigma_key*(nhist+1)/nhist
float R = (1+1/(float)Nhist)*lambda_descr*sigma_key;
float Rp = M_SQRT2*R;
int siMin = MAX(0, (int)(x_key - Rp +0.5));
int sjMin = MAX(0, (int)(y_key - Rp +0.5));
int siMax = MIN((int)(x_key + Rp +0.5), h-1);
int sjMax = MIN((int)(y_key + Rp +0.5), w-1);
/// For each pixel inside the patch.
for(int si = siMin; si < siMax; si++){
for(int sj = sjMin; sj < sjMax; sj++){
// Compute pixel coordinates (sX,sY) on keypoint's invariant referential.
float X = si - x_key;
float Y = sj - y_key;
apply_rotation(X, Y, &X, &Y, -theta_key);
// Does this sample fall inside the descriptor area ?
if (MAX(ABS(X),ABS(Y)) < R) {
// Compute the gradient orientation (theta) on keypoint referential.
double dx = imX[si*w+sj];
double dy = imY[si*w+sj];
float ori = atan2(dy, dx) - theta_key;
ori = modulus(ori, 2*M_PI);
// Compute the gradient magnitude and apply a Gaussian weighing to give less emphasis to distant sample
double t = lambda_descr*sigma_key;
double M = hypot(dx, dy) * exp(-(X*X+Y*Y)/(2*t*t));
// bin indices, Compute the (tri)linear weightings ...
float alpha = X/(2*lambda_descr*sigma_key/Nhist) + (Nhist-1.0)/2.0;
float beta = Y/(2*lambda_descr*sigma_key/Nhist) + (Nhist-1.0)/2.0;
float gamma = ori/(2*M_PI)*Nbins;
// ...and add contributions to respective bins in different histograms.
// a loop with 1 or two elements
int i0 = floor(alpha);
int j0 = floor(beta);
for(int i = MAX(0,i0);i<=MIN(i0+1,Nhist-1);i++){
for(int j = MAX(0,j0);j<=MIN(j0+1,Nhist-1);j++){ // looping through all surrounding histograms.
int k;
// Contribution to left bin.
k = ((int)gamma+Nbins)%Nbins;
descr[i*Nhist*Nbins+j*Nbins+k] += (1.-(gamma-floor(gamma)))
*(1.0-ABS((float)i-alpha))
*(1.0-ABS((float)j-beta))
*M;
// Contribution to right bin.
k = ((int)gamma+1+Nbins)%Nbins;
descr[i*Nhist*Nbins+j*Nbins+k] += (1.0-(floor(gamma)+1-gamma))
*(1.0-ABS((float)i-alpha))
*(1.0-ABS((float)j-beta))
*M;
}
}
}
}
}
}
/*
Rotates the tetrimino to the right (clockwise)
*/
void rotate_clockwise()
{
Tetrimino copy = *in_play;
copy.rotation = (copy.rotation + 1) % 4;
apply_rotation(copy);
}
