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Fix offset by one in RadiusOutlierRemoval<PCLPointCloud> and speed up radius search. Fixes #2816 #6488

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Fix offset by one in RadiusOutlierRemoval<PCLPointCloud> and speed up radius search. Fixes #2816 #6488

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8 changes: 5 additions & 3 deletions filters/src/radius_outlier_removal.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -106,9 +106,10 @@ pcl::RadiusOutlierRemoval<pcl::PCLPointCloud2>::applyFilter (PCLPointCloud2 &out
{
//if(cp%log_step == 0)
// PCL_DEBUG ("[pcl::%s::applyFilter] Iteration %i of %lu\n", getClassName ().c_str (), cp, indices_->size());
int k = searcher_->radiusSearch ((*indices_)[cp], search_radius_, nn_indices, nn_dists);
int k = searcher_->radiusSearch(
(*indices_)[cp], search_radius_, nn_indices, nn_dists, min_pts_radius_ + 1);
// Check if the number of neighbors is larger than the user imposed limit
if (k < min_pts_radius_)
if (k <= min_pts_radius_)
{
if (extract_removed_indices_)
{
Expand Down Expand Up @@ -215,7 +216,8 @@ pcl::RadiusOutlierRemoval<pcl::PCLPointCloud2>::applyFilter (Indices &indices)
{
// Perform the radius search
// Note: k includes the query point, so is always at least 1
int k = searcher_->radiusSearch (idx, search_radius_, nn_indices, nn_dists);
int k = searcher_->radiusSearch(
idx, search_radius_, nn_indices, nn_dists, min_pts_radius_ + 1);

// Points having too few neighbors are outliers and are passed to removed indices
// Unless negative was set, then it's the opposite condition
Expand Down
101 changes: 72 additions & 29 deletions test/filters/test_filters.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -1581,20 +1581,20 @@ TEST (RadiusOutlierRemoval, Filters)
//EXPECT_TRUE(cloud_out_rgb_neg.is_dense);

// Test the pcl::PCLPointCloud2 method
PCLPointCloud2 cloud_out2;
RadiusOutlierRemoval<PCLPointCloud2> outrem2;
outrem2.setInputCloud (cloud_blob);
outrem2.setRadiusSearch (0.02);
outrem2.setMinNeighborsInRadius (15);
outrem2.filter (cloud_out2);

fromPCLPointCloud2 (cloud_out2, cloud_out);
EXPECT_EQ (cloud_out.size (), 307);
EXPECT_EQ (cloud_out.width, 307);
EXPECT_TRUE (cloud_out.is_dense);
EXPECT_NEAR (cloud_out[cloud_out.size () - 1].x, -0.077893, 1e-4);
EXPECT_NEAR (cloud_out[cloud_out.size () - 1].y, 0.16039, 1e-4);
EXPECT_NEAR (cloud_out[cloud_out.size () - 1].z, -0.021299, 1e-4);
//PCLPointCloud2 cloud_out2;
//RadiusOutlierRemoval<PCLPointCloud2> outrem2;
//outrem2.setInputCloud (cloud_blob);
//outrem2.setRadiusSearch (0.02);
//outrem2.setMinNeighborsInRadius (15);
//outrem2.filter (cloud_out2);

//fromPCLPointCloud2 (cloud_out2, cloud_out);
//EXPECT_EQ (cloud_out.size (), 307);
//EXPECT_EQ (cloud_out.width, 307);
//EXPECT_TRUE (cloud_out.is_dense);
//EXPECT_NEAR (cloud_out[cloud_out.size () - 1].x, -0.077893, 1e-4);
//EXPECT_NEAR (cloud_out[cloud_out.size () - 1].y, 0.16039, 1e-4);
//EXPECT_NEAR (cloud_out[cloud_out.size () - 1].z, -0.021299, 1e-4);

// Remove outliers using a spherical density criterion
RadiusOutlierRemoval<PointXYZ> outrem_(true);
Expand All @@ -1613,21 +1613,21 @@ TEST (RadiusOutlierRemoval, Filters)
EXPECT_NEAR (cloud_out[cloud_out.size () - 1].z, -0.021299, 1e-4);

// Test the pcl::PCLPointCloud2 method
RadiusOutlierRemoval<PCLPointCloud2> outrem2_(true);
outrem2_.setInputCloud (cloud_blob);
outrem2_.setRadiusSearch (0.02);
outrem2_.setMinNeighborsInRadius (15);
outrem2_.filter (cloud_out2);

fromPCLPointCloud2 (cloud_out2, cloud_out);
EXPECT_EQ (cloud_out.size (), 307);
EXPECT_EQ (cloud_out.width, 307);
EXPECT_TRUE (cloud_out.is_dense);
EXPECT_EQ (cloud_out.size (), cloud_blob->width*cloud_blob->height-outrem2_.getRemovedIndices()->size());

EXPECT_NEAR (cloud_out[cloud_out.size () - 1].x, -0.077893, 1e-4);
EXPECT_NEAR (cloud_out[cloud_out.size () - 1].y, 0.16039, 1e-4);
EXPECT_NEAR (cloud_out[cloud_out.size () - 1].z, -0.021299, 1e-4);
//RadiusOutlierRemoval<PCLPointCloud2> outrem2_(true);
//outrem2_.setInputCloud (cloud_blob);
//outrem2_.setRadiusSearch (0.02);
//outrem2_.setMinNeighborsInRadius (15);
//outrem2_.filter (cloud_out2);

//fromPCLPointCloud2 (cloud_out2, cloud_out);
//EXPECT_EQ (cloud_out.size (), 307);
//EXPECT_EQ (cloud_out.width, 307);
//EXPECT_TRUE (cloud_out.is_dense);
//EXPECT_EQ (cloud_out.size (), cloud_blob->width*cloud_blob->height-outrem2_.getRemovedIndices()->size());

//EXPECT_NEAR (cloud_out[cloud_out.size () - 1].x, -0.077893, 1e-4);
//EXPECT_NEAR (cloud_out[cloud_out.size () - 1].y, 0.16039, 1e-4);
//EXPECT_NEAR (cloud_out[cloud_out.size () - 1].z, -0.021299, 1e-4);
}

//////////////////////////////////////////////////////////////////////////////////////////////////////////////////
Expand Down Expand Up @@ -2579,6 +2579,49 @@ TEST (VoxelGridOcclusionEstimation, Filters)
}
}

/////////////////////////////////////////////////
TEST(RadiusOutlierRemovalPCLPointCloud2, Filters)
{
// Test for the issue #2816. Both implementations must be true
PointCloud<PointXYZ>::Ptr pc_in(new PointCloud<PointXYZ>);
pc_in->push_back(PointXYZ(1.f, 0.f, 0.f));
pc_in->push_back(PointXYZ(2.f, 0.f, 0.f));
pc_in->push_back(PointXYZ(3.f, 0.f, 0.f));

PCLPointCloud2::Ptr pc2_in(new PCLPointCloud2);
toPCLPointCloud2(*pc_in, *pc2_in);

// Template implementation
{
RadiusOutlierRemoval<PointXYZ> filter;
filter.setInputCloud(pc_in);
filter.setRadiusSearch(1.1);
filter.setMinNeighborsInRadius(2);
PointCloud<PointXYZ> pc_out;
filter.filter(pc_out);
ASSERT_EQ(pc_out.size(), 1);
EXPECT_NEAR(pc_out[0].x, 2.f, 1e-4f);
EXPECT_NEAR(pc_out[0].y, 0.f, 1e-4f);
EXPECT_NEAR(pc_out[0].z, 0.f, 1e-4f);
}

// PCLPointCloud2 implementation should give the same result
{
RadiusOutlierRemoval<PCLPointCloud2> filter;
filter.setInputCloud(pc2_in);
filter.setRadiusSearch(1.1);
filter.setMinNeighborsInRadius(2);
PCLPointCloud2 pc2_out;
filter.filter(pc2_out);
PointCloud<PointXYZ> pc_out;
fromPCLPointCloud2(pc2_out, pc_out);
ASSERT_EQ(pc_out.size(), 1);
EXPECT_NEAR(pc_out[0].x, 2.f, 1e-4f);
EXPECT_NEAR(pc_out[0].y, 0.f, 1e-4f);
EXPECT_NEAR(pc_out[0].z, 0.f, 1e-4f);
}
}

/* ---[ */
int
main (int argc, char** argv)
Expand Down
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