void ComputeMSURFDescriptor(
const ImageT & Lx ,
const ImageT & Ly ,
const int id_octave ,
const SIOPointFeature & ipt ,
Descriptor< Real , 64 > & desc )
{
Real dx = 0, dy = 0, mdx = 0, mdy = 0, gauss_s1 = 0, gauss_s2 = 0;
Real rx = 0, ry = 0, rrx = 0, rry = 0, ys = 0, xs = 0;
Real sample_x = 0, sample_y = 0;
int kx = 0, ky = 0, i = 0, j = 0, dcount = 0;
// Subregion centers for the 4x4 gaussian weighting
Real cx = - static_cast<Real>( 0.5 ) , cy = static_cast<Real>( 0.5 ) ;
// Set the descriptor size and the sample and pattern sizes
const int sample_step = 5;
const int pattern_size = 12;
// Get the information from the keypoint
const Real ratio = static_cast<Real>( 1 << id_octave );
const int scale = MathTrait<float>::round( ipt.scale() / ratio );
const Real angle = ipt.orientation() ;
const Real yf = ipt.y() / ratio;
const Real xf = ipt.x() / ratio;
const Real co = MathTrait<Real>::cos( angle );
const Real si = MathTrait<Real>::sin( angle );
i = -8;
const image::Sampler2d<image::SamplerLinear> sampler;
// Calculate descriptor for this interest point
// Area of size 24 s x 24 s
while ( i < pattern_size )
{
j = -8;
i = i - 4;
cx += 1.0;
cy = -0.5;
while ( j < pattern_size )
{
dx = dy = mdx = mdy = 0.0;
cy += 1.0;
j = j - 4;
ky = i + sample_step;
kx = j + sample_step;
xs = xf + ( -kx * scale * si + ky * scale * co );
ys = yf + ( kx * scale * co + ky * scale * si );
for ( int k = i; k < i + 9; ++k )
{
for ( int l = j; l < j + 9; ++l )
{
// Get coords of sample point on the rotated axis
sample_y = yf + ( l * scale * co + k * scale * si );
sample_x = xf + ( -l * scale * si + k * scale * co );
// Get the gaussian weighted x and y responses
gauss_s1 = gaussian( xs - sample_x, ys - sample_y, static_cast<Real>( 2.5 ) * static_cast<Real>( scale ) );
rx = sampler( Lx, sample_y, sample_x );
ry = sampler( Ly, sample_y, sample_x );
// Get the x and y derivatives on the rotated axis
rry = gauss_s1 * ( rx * co + ry * si );
rrx = gauss_s1 * ( -rx * si + ry * co );
// Sum the derivatives to the cumulative descriptor
dx += rrx;
dy += rry;
mdx += MathTrait<Real>::abs( rrx );
mdy += MathTrait<Real>::abs( rry );
}
}
// Add the values to the descriptor vector
gauss_s2 = gaussian( cx - static_cast<Real>( 2.0 ) , cy - static_cast<Real>( 2.0 ) , static_cast<Real>( 1.5 ) ) ;
desc[dcount++] = dx * gauss_s2;
desc[dcount++] = dy * gauss_s2;
desc[dcount++] = mdx * gauss_s2;
desc[dcount++] = mdy * gauss_s2;
j += 9;
}
i += 9;
}
// convert to unit vector (L2 norm)
desc.normalize();
}
