/**
* {@link #icpGetInitXw2XcSub}関数のmat_dを計算します。
*/
private static NyARDoubleMatrix33 makeMatD(NyARDoubleMatrix44 i_cp, NyARDoublePoint2d[] pos2d, int i_num, NyARDoubleMatrix33 o_mat)
{
double m02 = 0;
double m12 = 0;
double m20 = 0;
double m21 = 0;
double m22 = 0;
for (int i = 0; i < i_num; i++)
{
double cx = i_cp.m02 - pos2d[i].x;
double cy = i_cp.m12 - pos2d[i].y;
m02 += (cx) * i_cp.m00;
m12 += (cx) * i_cp.m01 + (cy) * i_cp.m11;
m20 += i_cp.m00 * (cx);
m21 += i_cp.m01 * (cx) + i_cp.m11 * (cy);
m22 += (cx) * (cx) + (cy) * (cy);
}
o_mat.m00 = (i_cp.m00 * i_cp.m00) * i_num;
o_mat.m01 = (i_cp.m00 * i_cp.m01) * i_num;
o_mat.m02 = m02;
o_mat.m10 = (i_cp.m01 * i_cp.m00) * i_num;
o_mat.m11 = (i_cp.m01 * i_cp.m01 + i_cp.m11 * i_cp.m11) * i_num;
o_mat.m12 = m12;
o_mat.m20 = m20;
o_mat.m21 = m21;
o_mat.m22 = m22;
o_mat.inverse(o_mat);
return(o_mat);
}
/**
* {@link #icpGetInitXw2XcSub}関数のmat_dを計算します。
*/
private static NyARDoubleMatrix33 makeMatD(NyARDoubleMatrix44 i_cp, NyARDoublePoint2d[] pos2d, int i_num, NyARDoubleMatrix33 o_mat)
{
double m02 = 0;
double m12 = 0;
double m20 = 0;
double m21 = 0;
double m22 = 0;
for (int i = 0; i < i_num; i++)
{
double cx = i_cp.m02 - pos2d[i].x;
double cy = i_cp.m12 - pos2d[i].y;
m02 += (cx) * i_cp.m00;
m12 += (cx) * i_cp.m01 + (cy) * i_cp.m11;
m20 += i_cp.m00 * (cx);
m21 += i_cp.m01 * (cx) + i_cp.m11 * (cy);
m22 += (cx) * (cx) + (cy) * (cy);
}
o_mat.m00 = (i_cp.m00 * i_cp.m00) * i_num;
o_mat.m01 = (i_cp.m00 * i_cp.m01) * i_num;
o_mat.m02 = m02;
o_mat.m10 = (i_cp.m01 * i_cp.m00) * i_num;
o_mat.m11 = (i_cp.m01 * i_cp.m01 + i_cp.m11 * i_cp.m11) * i_num;
o_mat.m12 = m12;
o_mat.m20 = m20;
o_mat.m21 = m21;
o_mat.m22 = m22;
o_mat.inverse(o_mat);
return o_mat;
}
// private boolean ComputeSubpixelHessian(
// float H[9],float b[3],
// const Image& lap0,const Image& lap1,const Image& lap2,
// int x,int y)
private bool updateLocation(DogFeaturePoint kp, LaplacianImage lap0, LaplacianImage lap1, LaplacianImage lap2)
{
double[] tmp = new double[2];
double[] b = new double[3];
// Downsample the feature point to the detection octave
bilinear_downsample_point(tmp, kp.x, kp.y, kp.octave);
double xp = tmp[0];
double yp = tmp[1];
// Compute the discrete pixel location
int x = (int)(xp + 0.5f);
int y = (int)(yp + 0.5f);
double[] H = new double[9];
if (lap0.getWidth() == lap1.getWidth() && lap1.getWidth() == lap2.getWidth())
{
//すべての画像サイズが同じ
//assert lap0.getHeight() == lap1.getHeight() && lap1.getHeight() == lap2.getHeight();// "Width/height are not consistent");
ComputeSubpixelHessianSameOctave(H, b, lap0, lap1, lap2, x, y);
}
else if ((lap0.getWidth() == lap1.getWidth()) && ((lap1.getWidth() >> 1) == lap2.getWidth()))
{
//0,1が同じで2がその半分
//assert (lap0.getHeight() == lap1.getHeight()) && ((lap1.getHeight() >> 1) == lap2.getHeight());// Width/height are not consistent");
ComputeSubpixelHessianFineOctavePair(H, b, lap0, lap1, lap2, x, y);
}
else if (((lap0.getWidth() >> 1) == lap1.getWidth()) && (lap1.getWidth() == lap2.getWidth()))
{
//0の半分が1,2
//assert ((lap0.getWidth() >> 1) == lap1.getWidth()) && (lap1.getWidth() == lap2.getWidth());// Width/height are not consistent");
ComputeSubpixelHessianCoarseOctavePair(H, b, lap0, lap1, lap2, x, y);
}
else
{
// ASSERT(0, "Image sizes are inconsistent");
return(false);
}
// A*u=b // if (!SolveSymmetricLinearSystem3x3(u, H, b)) {
NyARDoubleMatrix33 m = new NyARDoubleMatrix33();
m.m00 = H[0];
m.m01 = H[1];
m.m02 = H[2];
m.m10 = H[3];
m.m11 = H[4];
m.m12 = H[5];
m.m20 = H[6];
m.m21 = H[7];
m.m22 = H[8];
if (!m.inverse(m))
{
return(false);
}
double u0 = (m.m00 * b[0] + m.m01 * b[1] + m.m02 * b[2]);
double u1 = (m.m10 * b[0] + m.m11 * b[1] + m.m12 * b[2]);
double u2 = (m.m20 * b[0] + m.m21 * b[1] + m.m22 * b[2]);
// If points move too much in the sub-pixel update, then the point probably unstable.
if ((u0 * u0) + (u1 * u1) > mMaxSubpixelDistanceSqr)
{
return(false);
}
// Compute the edge score
if (!ComputeEdgeScore(tmp, H))
{
return(false);
}
kp.edge_score = tmp[0];
// Compute a linear estimate of the intensity
// ASSERT(kp.score == lap1.get<float>(y)[x],
// "Score is not consistent with the DoG image");
double[] lap1_buf = (double[])lap1.getBuffer();
kp.score = lap1_buf[lap1.get(y) + x] - (b[0] * u0 + b[1] * u1 + b[2] * u2);
// Update the location:
// Apply the update on the downsampled location and then upsample
// the result.
// bilinear_upsample_point(kp.x, kp.y, xp+u[0], yp+u[1], kp.octave);
bilinear_upsample_point(tmp, xp + u0, yp + u1, kp.octave);
kp.x = tmp[0];
kp.y = tmp[1];
// Update the scale
kp.sp_scale = kp.scale + u2;
kp.sp_scale = ClipScalar(kp.sp_scale, 0, mLaplacianPyramid.numScalePerOctave());
return(true);
}