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Commit 905fd903 authored by Davis King's avatar Davis King
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Changed the hessian_pyramid so that it has a slightly smaller border 

region and therefore finds more interest points.
parent ddaefb6c
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Showing with 35 additions and 42 deletions
dlib/image_keypoint/hessian_pyramid.h
View file @ 905fd903
......@@ -119,10 +119,10 @@ namespace dlib
for (long o = 0; o < num_octaves; ++o)
{
const long step_size = get_step_size(o);
const long border_size = get_border_size(o)*step_size;
for (long i = 0; i < num_intervals; ++i)
{
const long border_size = get_border_size(i)*step_size;
const long lobe_size = static_cast<long>(std::pow(2.0, o+1.0)+0.5)*(i+1) + 1;
const double area_inv = 1.0/std::pow(3.0*lobe_size, 2.0);
......@@ -178,17 +178,17 @@ namespace dlib
}
long get_border_size (
long octave
long interval
) const
{
DLIB_ASSERT(0 <= octave && octave < octaves(),
"\tlong get_border_size(octave)"
<< "\n\tInvalid octave value"
DLIB_ASSERT(0 <= interval && interval < intervals(),
"\tlong get_border_size(interval)"
<< "\n\tInvalid interval value"
<< "\n\t this: " << this
<< "\n\t octave: " << octave
<< "\n\t interval: " << interval
);
const double lobe_size = std::pow(2.0, octave+1.0)*(num_intervals+1) + 1;
const double lobe_size = 2.0*(interval+1) + 1;
const double filter_size = 3*lobe_size;
const long bs = static_cast<long>(std::ceil(filter_size/2.0));
......@@ -246,8 +246,8 @@ namespace dlib
{
DLIB_ASSERT(0 <= octave && octave < octaves() &&
0 <= interval && interval < intervals() &&
get_border_size(octave) <= r && r < nr(octave)-get_border_size(octave) &&
get_border_size(octave) <= c && c < nc(octave)-get_border_size(octave),
get_border_size(interval) <= r && r < nr(octave)-get_border_size(interval) &&
get_border_size(interval) <= c && c < nc(octave)-get_border_size(interval),
"\tdouble get_value(octave, interval, r, c)"
<< "\n\tInvalid inputs to this function"
<< "\n\t this: " << this
......@@ -259,7 +259,7 @@ namespace dlib
<< "\n\t c: " << c
<< "\n\t nr(octave): " << nr(octave)
<< "\n\t nc(octave): " << nc(octave)
<< "\n\t get_border_size(octave): " << get_border_size(octave)
<< "\n\t get_border_size(interval): " << get_border_size(interval)
);
return std::abs(pyramid[num_intervals*octave + interval][r][c]);
......@@ -274,8 +274,8 @@ namespace dlib
{
DLIB_ASSERT(0 <= octave && octave < octaves() &&
0 <= interval && interval < intervals() &&
get_border_size(octave) <= r && r < nr(octave)-get_border_size(octave) &&
get_border_size(octave) <= c && c < nc(octave)-get_border_size(octave),
get_border_size(interval) <= r && r < nr(octave)-get_border_size(interval) &&
get_border_size(interval) <= c && c < nc(octave)-get_border_size(interval),
"\tdouble get_laplacian(octave, interval, r, c)"
<< "\n\tInvalid inputs to this function"
<< "\n\t this: " << this
......@@ -287,7 +287,7 @@ namespace dlib
<< "\n\t c: " << c
<< "\n\t nr(octave): " << nr(octave)
<< "\n\t nc(octave): " << nc(octave)
<< "\n\t get_border_size(octave): " << get_border_size(octave)
<< "\n\t get_border_size(interval): " << get_border_size(interval)
);
// return the sign of the laplacian
......@@ -436,6 +436,11 @@ namespace dlib
temp.score = pyr.get_value(o,i,r,c);
temp.laplacian = pyr.get_laplacian(o,i,r,c);
}
else
{
// this indicates to the caller that no interest point was found.
temp.score = -1;
}
return temp;
}
......@@ -469,43 +474,26 @@ namespace dlib
// do non-maximum suppression on all the intervals in the current octave and
// accumulate the results in result_points
for (long i = 1; i < pyr.intervals()-1; i += 3)
for (long i = 1; i < pyr.intervals()-1; i += 1)
{
for (long r = border_size+1; r < nr - border_size-1; r += 3)
const long border_size = pyr.get_border_size(i+1);
for (long r = border_size+1; r < nr - border_size-1; r += 1)
{
for (long c = border_size+1; c < nc - border_size-1; c += 3)
for (long c = border_size+1; c < nc - border_size-1; c += 1)
{
double max_val = pyr.get_value(o,i,r,c);
long max_i = i;
long max_r = r;
long max_c = c;
// loop over this 3x3x3 block and find the largest element
for (long ii = i; ii < std::min(i + 3, pyr.intervals()-1); ++ii)
{
for (long rr = r; rr < std::min(r + 3, nr - border_size - 1); ++rr)
{
for (long cc = c; cc < std::min(c + 3, nc - border_size - 1); ++cc)
{
double temp = pyr.get_value(o,ii,rr,cc);
if (temp > max_val)
{
max_val = temp;
max_i = ii;
max_r = rr;
max_c = cc;
}
}
}
}
// If the max point we found is really a maximum in its own region and
// is big enough then add it to the results.
if (max_val > threshold && is_maximum_in_region(pyr, o, max_i, max_r, max_c))
if (max_val >= threshold && is_maximum_in_region(pyr, o, max_i, max_r, max_c))
{
//cout << max_val << endl;
interest_point sp = interpolate_point (pyr, o, max_i, max_r, max_c);
if (sp.score > threshold)
if (sp.score >= threshold)
{
result_points.push_back(sp);
}
......
dlib/image_keypoint/hessian_pyramid_abstract.h
View file @ 905fd903
......@@ -73,13 +73,13 @@ namespace dlib
!*/
long get_border_size (
long octave
long interval
) const;
/*!
requires
- 0 <= octave < octaves()
- 0 <= interval < intervals()
ensures
- Each octave of the pyramid has a certain sized border region where we
- Each interval of the pyramid has a certain sized border region where we
can't compute the Hessian values since they are too close to the edge
of the input image. This function returns the size of that border.
!*/
......@@ -129,7 +129,7 @@ namespace dlib
requires
- 0 <= octave < octaves()
- 0 <= interval < intervals()
- Let BS == get_border_size(octave): then
- Let BS == get_border_size(interval): then
- BS <= r < nr(octave)-BS
- BS <= c < nc(octave)-BS
ensures
......@@ -148,7 +148,7 @@ namespace dlib
requires
- 0 <= octave < octaves()
- 0 <= interval < intervals()
- Let BS == get_border_size(octave): then
- Let BS == get_border_size(interval): then
- BS <= r < nr(octave)-BS
- BS <= c < nc(octave)-BS
ensures
......@@ -175,7 +175,12 @@ namespace dlib
- center == the x/y location of the center of the interest point
(in image space coordinates. y gives the row and x gives the
column in the image)
- scale == the scale at which the point was detected
- scale == the scale at which the point was detected. This is a number
>= 1. If it is 1 then it means the interest point was detected at
the lowest scale in the image pyramid. Larger numbers indicate that
the interest point is from high up in the image pyramid. For
example, a scale of 4 would mean the interest point was located at a
point in the pyramid where the image had been shrunk by a factor of 4.
- score == the determinant of the Hessian for the interest point
- laplacian == the sign of the laplacian for the interest point
!*/
......
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