trajkovic_2d.hpp
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#ifndef PCL_TRAJKOVIC_KEYPOINT_2D_IMPL_H_
#define PCL_TRAJKOVIC_KEYPOINT_2D_IMPL_H_
template <typename PointInT, typename PointOutT, typename IntensityT> bool
pcl::TrajkovicKeypoint2D<PointInT, PointOutT, IntensityT>::initCompute ()
{
if (!PCLBase<PointInT>::initCompute ())
return (false);
keypoints_indices_.reset (new pcl::PointIndices);
keypoints_indices_->indices.reserve (input_->size ());
if (!input_->isOrganized ())
{
PCL_ERROR ("[pcl::%s::initCompute] %s doesn't support non organized clouds!\n", name_.c_str ());
return (false);
}
if (indices_->size () != input_->size ())
{
PCL_ERROR ("[pcl::%s::initCompute] %s doesn't support setting indices!\n", name_.c_str ());
return (false);
}
if ((window_size_%2) == 0)
{
PCL_ERROR ("[pcl::%s::initCompute] Window size must be odd!\n", name_.c_str ());
return (false);
}
if (window_size_ < 3)
{
PCL_ERROR ("[pcl::%s::initCompute] Window size must be >= 3x3!\n", name_.c_str ());
return (false);
}
half_window_size_ = window_size_ / 2;
return (true);
}
/////////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointOutT, typename IntensityT> void
pcl::TrajkovicKeypoint2D<PointInT, PointOutT, IntensityT>::detectKeypoints (PointCloudOut &output)
{
response_.reset (new pcl::PointCloud<float> (input_->width, input_->height));
int w = static_cast<int> (input_->width) - half_window_size_;
int h = static_cast<int> (input_->height) - half_window_size_;
if (method_ == pcl::TrajkovicKeypoint2D<PointInT, PointOutT, IntensityT>::FOUR_CORNERS)
{
#ifdef _OPENMP
#pragma omp parallel for num_threads (threads_)
#endif
for(int j = half_window_size_; j < h; ++j)
{
for(int i = half_window_size_; i < w; ++i)
{
float center = intensity_ ((*input_) (i,j));
float up = intensity_ ((*input_) (i, j-half_window_size_));
float down = intensity_ ((*input_) (i, j+half_window_size_));
float left = intensity_ ((*input_) (i-half_window_size_, j));
float right = intensity_ ((*input_) (i+half_window_size_, j));
float up_center = up - center;
float r1 = up_center * up_center;
float down_center = down - center;
r1+= down_center * down_center;
float right_center = right - center;
float r2 = right_center * right_center;
float left_center = left - center;
r2+= left_center * left_center;
float d = std::min (r1, r2);
if (d < first_threshold_)
continue;
float b1 = (right - up) * up_center;
b1+= (left - down) * down_center;
float b2 = (right - down) * down_center;
b2+= (left - up) * up_center;
float B = std::min (b1, b2);
float A = r2 - r1 - 2*B;
(*response_) (i,j) = ((B < 0) && ((B + A) > 0)) ? r1 - ((B*B)/A) : d;
}
}
}
else
{
#ifdef _OPENMP
#pragma omp parallel for num_threads (threads_)
#endif
for(int j = half_window_size_; j < h; ++j)
{
for(int i = half_window_size_; i < w; ++i)
{
float center = intensity_ ((*input_) (i,j));
float up = intensity_ ((*input_) (i, j-half_window_size_));
float down = intensity_ ((*input_) (i, j+half_window_size_));
float left = intensity_ ((*input_) (i-half_window_size_, j));
float right = intensity_ ((*input_) (i+half_window_size_, j));
float upleft = intensity_ ((*input_) (i-half_window_size_, j-half_window_size_));
float upright = intensity_ ((*input_) (i+half_window_size_, j-half_window_size_));
float downleft = intensity_ ((*input_) (i-half_window_size_, j+half_window_size_));
float downright = intensity_ ((*input_) (i+half_window_size_, j+half_window_size_));
std::vector<float> r (4,0);
float up_center = up - center;
r[0] = up_center * up_center;
float down_center = down - center;
r[0]+= down_center * down_center;
float upright_center = upright - center;
r[1] = upright_center * upright_center;
float downleft_center = downleft - center;
r[1]+= downleft_center * downleft_center;
float right_center = right - center;
r[2] = right_center * right_center;
float left_center = left - center;
r[2]+= left_center * left_center;
float downright_center = downright - center;
r[3] = downright_center * downright_center;
float upleft_center = upleft - center;
r[3]+= upleft_center * upleft_center;
float d = *(std::min_element (r.begin (), r.end ()));
if (d < first_threshold_)
continue;
std::vector<float> B (4,0);
std::vector<float> A (4,0);
std::vector<float> sumAB (4,0);
B[0] = (upright - up) * up_center;
B[0]+= (downleft - down) * down_center;
B[1] = (right - upright) * upright_center;
B[1]+= (left - downleft) * downleft_center;
B[2] = (downright - right) * downright_center;
B[2]+= (upleft - left) * upleft_center;
B[3] = (down - downright) * downright_center;
B[3]+= (up - upleft) * upleft_center;
A[0] = r[1] - r[0] - B[0] - B[0];
A[1] = r[2] - r[1] - B[1] - B[1];
A[2] = r[3] - r[2] - B[2] - B[2];
A[3] = r[0] - r[3] - B[3] - B[3];
sumAB[0] = A[0] + B[0];
sumAB[1] = A[1] + B[1];
sumAB[2] = A[2] + B[2];
sumAB[3] = A[3] + B[3];
if ((*std::max_element (B.begin (), B.end ()) < 0) &&
(*std::min_element (sumAB.begin (), sumAB.end ()) > 0))
{
std::vector<float> D (4,0);
D[0] = B[0] * B[0] / A[0];
D[1] = B[1] * B[1] / A[1];
D[2] = B[2] * B[2] / A[2];
D[3] = B[3] * B[3] / A[3];
(*response_) (i,j) = *(std::min (D.begin (), D.end ()));
}
else
(*response_) (i,j) = d;
}
}
}
// Non maximas suppression
std::vector<int> indices = *indices_;
std::sort (indices.begin (), indices.end (),
boost::bind (&TrajkovicKeypoint2D::greaterCornernessAtIndices, this, _1, _2));
output.clear ();
output.reserve (input_->size ());
std::vector<bool> occupency_map (indices.size (), false);
const int width (input_->width);
const int height (input_->height);
#ifdef _OPENMP
#pragma omp parallel for shared (output) num_threads (threads_)
#endif
for (size_t i = 0; i < indices.size (); ++i)
{
int idx = indices[i];
if ((response_->points[idx] < second_threshold_) || occupency_map[idx])
continue;
PointOutT p;
p.getVector3fMap () = input_->points[idx].getVector3fMap ();
p.intensity = response_->points [idx];
#ifdef _OPENMP
#pragma omp critical
#endif
{
output.push_back (p);
keypoints_indices_->indices.push_back (idx);
}
const int x = idx % width;
const int y = idx / width;
const int u_end = std::min (width, x + half_window_size_);
const int v_end = std::min (height, y + half_window_size_);
for(int v = std::max (0, y - half_window_size_); v < v_end; ++v)
for(int u = std::max (0, x - half_window_size_); u < u_end; ++u)
occupency_map[v*width + u] = true;
}
output.height = 1;
output.width = static_cast<uint32_t> (output.size());
// we don not change the denseness
output.is_dense = input_->is_dense;
}
#define PCL_INSTANTIATE_TrajkovicKeypoint2D(T,U,I) template class PCL_EXPORTS pcl::TrajkovicKeypoint2D<T,U,I>;
#endif
pcl::PointCloud::reserve
void reserve(size_t n)
Definition: point_cloud.h:449
pcl::TrajkovicKeypoint2D::detectKeypoints
void detectKeypoints(PointCloudOut &output)
Abstract key point detection method.
Definition: trajkovic_2d.hpp:81
pcl::PointCloud::push_back
void push_back(const PointT &pt)
Insert a new point in the cloud, at the end of the container.
Definition: point_cloud.h:480
pcl::TrajkovicKeypoint2D::initCompute
bool initCompute()
Definition: trajkovic_2d.hpp:42
pcl::TrajkovicKeypoint2D
TrajkovicKeypoint2D implements Trajkovic and Hedley corner detector on organized pooint cloud using i...
Definition: trajkovic_2d.h:55
pcl::PointCloud::height
uint32_t height
The point cloud height (if organized as an image-structure).
Definition: point_cloud.h:415
pcl::PointCloud::width
uint32_t width
The point cloud width (if organized as an image-structure).
Definition: point_cloud.h:413
pcl::PointIndices
Definition: PointIndices.h:12
pcl::PCLBase
PCL base class.
Definition: pcl_base.h:68
pcl::PointCloud::clear
void clear()
Removes all points in a cloud and sets the width and height to 0.
Definition: point_cloud.h:575
pcl::PointCloud
PointCloud represents the base class in PCL for storing collections of 3D points. ...
Definition: projection_matrix.h:53
pcl::PointCloud::is_dense
bool is_dense
True if no points are invalid (e.g., have NaN or Inf values).
Definition: point_cloud.h:418
pcl::B
Definition: norms.h:55
pcl::PointCloud::size
size_t size() const
Definition: point_cloud.h:448