diff --git a/lib/libstereo/CMakeLists.txt b/lib/libstereo/CMakeLists.txt
index 64e19cd84f2ec398fad46ab9c1c64e751bbeab17..47a6aa69fe65fc5c1d542c47ea5f4721658fb2ff 100644
--- a/lib/libstereo/CMakeLists.txt
+++ b/lib/libstereo/CMakeLists.txt
@@ -46,7 +46,8 @@ if (LIBSTEREO_SHARED)
src/algorithms/hwcensussgm.cu
src/algorithms/brefcensussgm.cu
src/algorithms/meancensussgm.cu
- src/algorithms/hstablesgm.cu
+ src/algorithms/hstablesgm.cu
+ src/algorithms/clustersf.cu
#src/stereo_hier_census.cu
src/stereo_wcensussgm.cu
src/stereo_census_adaptive.cu
@@ -82,7 +83,8 @@ else()
src/algorithms/hwcensussgm.cu
src/algorithms/brefcensussgm.cu
src/algorithms/meancensussgm.cu
- src/algorithms/hstablesgm.cu
+ src/algorithms/hstablesgm.cu
+ src/algorithms/clustersf.cu
#src/stereo_hier_census.cu
src/stereo_wcensussgm.cu
src/stereo_census_adaptive.cu
diff --git a/lib/libstereo/include/stereo.hpp b/lib/libstereo/include/stereo.hpp
index c596986b02bf3243f15a4f00db4b919a2fa062db..d0a2e6e928ea07be880027ab73f885c549746b6c 100644
--- a/lib/libstereo/include/stereo.hpp
+++ b/lib/libstereo/include/stereo.hpp
@@ -188,6 +188,25 @@ private:
Impl *impl_;
};
+/* Clustered Salient Features with focal point */
+class StereoCSF {
+public:
+ StereoCSF();
+ ~StereoCSF();
+
+ void compute(cv::InputArray l, cv::InputArray r, cv::OutputArray disparity);
+ void setPrior(cv::InputArray disp) {};
+
+ struct Parameters {
+ bool debug = false;
+ };
+ Parameters params;
+
+private:
+ struct Impl;
+ Impl *impl_;
+};
+
/**
* STABLE Binary descriptor. This is a general implementation.
*
diff --git a/lib/libstereo/middlebury/algorithms.hpp b/lib/libstereo/middlebury/algorithms.hpp
index 604f0f57c73529ffa5ae6b88b9a42465f6e51a3f..7c0d2ca4bf9a7f51d6ece71629dd9ab754fd0be1 100644
--- a/lib/libstereo/middlebury/algorithms.hpp
+++ b/lib/libstereo/middlebury/algorithms.hpp
@@ -32,6 +32,15 @@ namespace Impl {
}
};
+ struct ClusterSF : public Algorithm {
+ ClusterSF() { }
+
+ virtual void run(const MiddleburyData &data, cv::Mat &disparity) override {
+ StereoCSF stereo;
+ stereo.compute(data.imL, data.imR, disparity);
+ }
+ };
+
struct ECensusSGM : public Algorithm {
ECensusSGM() { P1 = 8.0f; P2 = 40.0f; } // Tuned to total error 2.0
@@ -341,6 +350,7 @@ namespace Impl {
static const std::map<std::string, Algorithm*> algorithms = {
{ "censussgm", new Impl::CensusSGM() },
+ { "cluster", new Impl::ClusterSF() },
{ "mcensussgm", new Impl::MeanCensusSGM() },
{ "gcensussgm", new Impl::GCensusSGM() },
{ "ecensussgm", new Impl::ECensusSGM() },
diff --git a/lib/libstereo/src/algorithms/clustersf.cu b/lib/libstereo/src/algorithms/clustersf.cu
new file mode 100644
index 0000000000000000000000000000000000000000..454a42b3cb3db9b5f579160b3255c2b638dee260
--- /dev/null
+++ b/lib/libstereo/src/algorithms/clustersf.cu
@@ -0,0 +1,52 @@
+#include "stereo.hpp"
+#include "stereosgm.hpp"
+#include "../filters/salient_gradient.hpp"
+
+#include <opencv2/highgui.hpp>
+
+struct StereoCSF::Impl {
+ Array2D<uchar> l;
+ Array2D<uchar> r;
+ Array2D<uchar> gl;
+ Array2D<uchar> gr;
+ Array2D<uchar> temp;
+
+ Impl(int width, int height) :
+ l(width, height), r(width, height),
+ gl(width, height), gr(width, height), temp(width, height) {}
+};
+
+StereoCSF::StereoCSF() : impl_(nullptr) {
+ impl_ = new Impl(0, 0);
+}
+
+void StereoCSF::compute(cv::InputArray l, cv::InputArray r, cv::OutputArray disparity) {
+
+ //cudaSetDevice(0);
+
+ if (l.rows() != impl_->l.height || r.cols() != impl_->l.width) {
+ delete impl_; impl_ = nullptr;
+ impl_ = new Impl(l.cols(), l.rows());
+ }
+
+ mat2gray(l, impl_->l);
+ mat2gray(r, impl_->r);
+
+ SalientGradient sg = {impl_->l.data(), impl_->gl.data(), impl_->temp.data(), impl_->l.width, impl_->l.height};
+ parallel1DWarp(sg, l.rows(), l.cols());
+
+ cv::Mat tmp;
+ impl_->gl.toGpuMat().download(tmp);
+ cv::imshow("Gradients", tmp);
+
+ cudaSafeCall(cudaDeviceSynchronize());
+ disparity.create(l.rows(), l.cols(), CV_32F);
+}
+
+StereoCSF::~StereoCSF() {
+ if (impl_) {
+ delete impl_;
+ impl_ = nullptr;
+ }
+}
+
diff --git a/lib/libstereo/src/filters/salient_gradient.hpp b/lib/libstereo/src/filters/salient_gradient.hpp
new file mode 100644
index 0000000000000000000000000000000000000000..fd521d1742d886c2a26ce7552dd9473ea72e8d2d
--- /dev/null
+++ b/lib/libstereo/src/filters/salient_gradient.hpp
@@ -0,0 +1,56 @@
+#ifndef _FTL_LIBSTEREO_FILTERS_SALIENT_GRADIENT_HPP_
+#define _FTL_LIBSTEREO_FILTERS_SALIENT_GRADIENT_HPP_
+
+#include "../util.hpp"
+#include "../array2d.hpp"
+
+struct SalientGradient {
+ Array2D<uchar>::Data image;
+ Array2D<uchar>::Data output;
+ Array2D<uchar>::Data magnitude;
+
+ int width, height;
+
+ __cuda__ inline float2 calculateGradient(int x, int y) {
+ if (x < 1 || y < 1 || x >= width-1 || y >= height-1) return make_float2(0,0);
+
+ float dx = -1.0f*float(image(y-1,x-1)) + -2.0f*float(image(y, x-1)) + -1*float(image(y+1, x-1)) +
+ float(image(y-1, x+1)) + 2.0f*float(image(y, x+1)) + float(image(y+1, x+1));
+ float dy = float(image(y-1, x-1)) + 2.0f*float(image(y-1, x)) + float(image(y-1, x+1)) +
+ -1.0f*float(image(y+1, x-1)) + -2.0f*float(image(y+1, x)) + -1.0f*float(image(y+1, x+1));
+
+ float g = sqrt( (dx*dx) + (dy*dy) );
+ float a = atan2(dy, dx);
+ return make_float2(g,a);
+ }
+
+ __device__ void operator()(ushort2 thread, ushort2 stride, ushort2 size) {
+ static const float PI = 3.14f;
+ static constexpr float PI2 = PI/2.0f;
+
+ for (int y=thread.y; y<size.y; y+=stride.y) {
+ for (int x=thread.x; x<size.x; x+=stride.x) {
+ auto g = calculateGradient(x,y);
+ output(y,x) = uchar((g.y+PI2) / PI * 255.0f);
+ magnitude(y,x) = uchar(g.x);
+ }
+
+ __syncwarp();
+
+ // Apply threshold
+ for (int x=thread.x; x<size.x; x+=stride.x) {
+ uchar thresh = 0;
+ for (int u=-15; u<=15; ++u) {
+ thresh = (x+u >= 0 && x+u < width) ? max(thresh, magnitude(y,x+u)-abs(u)) : thresh;
+ }
+
+ uchar m = magnitude(y,x);
+ if (m < thresh) output(y,x) = 0;
+ }
+
+ // Next step would be to bucket the results
+ }
+ }
+};
+
+#endif