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precompute feature response for scaling factor

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marina.kolpakova
2012-09-20 16:44:38 +04:00
parent 267d140bfe
commit 2b7ce8b160
1 changed files with 36 additions and 0 deletions
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36
modules/gpu/src/softcascade.cpp
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@@ -252,6 +252,40 @@ inline bool cv::gpu::SoftCascade::Filds::fill(const FileNode &root, const float
return true;
}
namespace {
struct CascadeIntrinsics
{
static const float lambda = 1.099f, a = 0.89f;
static float getFor(int channel, float scaling)
{
CV_Assert(channel < 10);
if (fabs(scaling - 1.f) < FLT_EPSILON)
return 1.f;
// according to R. Benenson, M. Mathias, R. Timofte and L. Van Gool's and Dallal's papers
static const float A[2][2] =
{ //channel <= 6, otherwise
{ 0.89f, 1.f}, // down
{ 1.00f, 1.f} // up
};
static const float B[2][2] =
{ //channel <= 6, otherwise
{ 1.099f / log(2), 2.f}, // down
{ 0.f, 2.f} // up
};
float a = A[(int)(scaling >= 1)][(int)(channel > 6)];
float b = B[(int)(scaling >= 1)][(int)(channel > 6)];
printf("!!! scaling: %f %f %f -> %f\n", scaling, a, b, a * pow(scaling, b));
return a * pow(scaling, b);
}
};
}
inline void cv::gpu::SoftCascade::Filds::calcLevels(const std::vector<icf::Octave>& octs,
int frameW, int frameH, int nscales)
{
@@ -270,6 +304,8 @@ inline void cv::gpu::SoftCascade::Filds::calcLevels(const std::vector<icf::Octav
int fit = fitOctave(octs, logScale);
icf::Level level(fit, octs[fit], scale, width, height);
level.scaling[0] = CascadeIntrinsics::getFor(0, level.relScale);
level.scaling[1] = CascadeIntrinsics::getFor(9, level.relScale);
if (!width || !height)
break;