Increased version to 0.9.0. Refactoring: Split util3d.h into multiple files util3d_****.h to reduce compilation time. Also removed all PCL templates to reduce memory used while compiling.

2026-10-07 02:27:47 +08:00 · 2015-05-13 19:54:23 -04:00
parent b54ff8547e
commit 9fde57843f
39 changed files with 4819 additions and 3644 deletions
@@ -0,0 +1,156 @@
+/*
+Copyright (c) 2010-2014, Mathieu Labbe - IntRoLab - Universite de Sherbrooke
+All rights reserved.
+
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
+    * Redistributions of source code must retain the above copyright
+      notice, this list of conditions and the following disclaimer.
+    * Redistributions in binary form must reproduce the above copyright
+      notice, this list of conditions and the following disclaimer in the
+      documentation and/or other materials provided with the distribution.
+    * Neither the name of the Universite de Sherbrooke nor the
+      names of its contributors may be used to endorse or promote products
+      derived from this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY
+DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+*/
+
+#include "rtabmap/core/util3d_surface.h"
+#include "rtabmap/core/util3d_filtering.h"
+#include <pcl/search/kdtree.h>
+#include <pcl/surface/gp3.h>
+#include <pcl/features/normal_3d_omp.h>
+#include <pcl/surface/mls.h>
+
+namespace rtabmap
+{
+
+namespace util3d
+{
+
+pcl::PolygonMesh::Ptr createMesh(
+		const pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr & cloudWithNormals,
+		float gp3SearchRadius,
+		float gp3Mu,
+		int gp3MaximumNearestNeighbors,
+		float gp3MaximumSurfaceAngle,
+		float gp3MinimumAngle,
+		float gp3MaximumAngle,
+		bool gp3NormalConsistency)
+{
+	pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr cloudWithNormalsNoNaN = removeNaNNormalsFromPointCloud(cloudWithNormals);
+
+	// Create search tree*
+	pcl::search::KdTree<pcl::PointXYZRGBNormal>::Ptr tree2 (new pcl::search::KdTree<pcl::PointXYZRGBNormal>);
+	tree2->setInputCloud (cloudWithNormalsNoNaN);
+
+	// Initialize objects
+	pcl::GreedyProjectionTriangulation<pcl::PointXYZRGBNormal> gp3;
+	pcl::PolygonMesh::Ptr mesh(new pcl::PolygonMesh);
+
+	// Set the maximum distance between connected points (maximum edge length)
+	gp3.setSearchRadius (gp3SearchRadius);
+
+	// Set typical values for the parameters
+	gp3.setMu (gp3Mu);
+	gp3.setMaximumNearestNeighbors (gp3MaximumNearestNeighbors);
+	gp3.setMaximumSurfaceAngle(gp3MaximumSurfaceAngle); // 45 degrees
+	gp3.setMinimumAngle(gp3MinimumAngle); // 10 degrees
+	gp3.setMaximumAngle(gp3MaximumAngle); // 120 degrees
+	gp3.setNormalConsistency(gp3NormalConsistency);
+
+	// Get result
+	gp3.setInputCloud (cloudWithNormalsNoNaN);
+	gp3.setSearchMethod (tree2);
+	gp3.reconstruct (*mesh);
+
+	return mesh;
+}
+
+pcl::PointCloud<pcl::PointNormal>::Ptr computeNormals(
+		const pcl::PointCloud<pcl::PointXYZ>::Ptr & cloud,
+		int normalKSearch)
+{
+	pcl::PointCloud<pcl::PointNormal>::Ptr cloud_with_normals(new pcl::PointCloud<pcl::PointNormal>);
+	pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>);
+	tree->setInputCloud (cloud);
+
+	// Normal estimation*
+	pcl::NormalEstimationOMP<pcl::PointXYZ, pcl::Normal> n;
+	pcl::PointCloud<pcl::Normal>::Ptr normals (new pcl::PointCloud<pcl::Normal>);
+	n.setInputCloud (cloud);
+	n.setSearchMethod (tree);
+	n.setKSearch (normalKSearch);
+	n.compute (*normals);
+	//* normals should not contain the point normals + surface curvatures
+
+	// Concatenate the XYZ and normal fields*
+	pcl::concatenateFields (*cloud, *normals, *cloud_with_normals);
+	//* cloud_with_normals = cloud + normals*/
+
+	return cloud_with_normals;
+}
+
+pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr computeNormals(
+		const pcl::PointCloud<pcl::PointXYZRGB>::Ptr & cloud,
+		int normalKSearch)
+{
+	pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr cloud_with_normals(new pcl::PointCloud<pcl::PointXYZRGBNormal>);
+	pcl::search::KdTree<pcl::PointXYZRGB>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZRGB>);
+	tree->setInputCloud (cloud);
+
+	// Normal estimation*
+	pcl::NormalEstimationOMP<pcl::PointXYZRGB, pcl::Normal> n;
+	pcl::PointCloud<pcl::Normal>::Ptr normals (new pcl::PointCloud<pcl::Normal>);
+	n.setInputCloud (cloud);
+	n.setSearchMethod (tree);
+	n.setKSearch (normalKSearch);
+	n.compute (*normals);
+	//* normals should not contain the point normals + surface curvatures
+
+	// Concatenate the XYZ and normal fields*
+	pcl::concatenateFields (*cloud, *normals, *cloud_with_normals);
+	//* cloud_with_normals = cloud + normals*/
+
+	return cloud_with_normals;
+}
+
+pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr computeNormalsSmoothed(
+		const pcl::PointCloud<pcl::PointXYZRGB>::Ptr & cloud,
+		float smoothingSearchRadius,
+		bool smoothingPolynomialFit)
+{
+	pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr cloud_with_normals(new pcl::PointCloud<pcl::PointXYZRGBNormal>);
+	pcl::search::KdTree<pcl::PointXYZRGB>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZRGB>);
+	tree->setInputCloud (cloud);
+
+	// Init object (second point type is for the normals, even if unused)
+	pcl::MovingLeastSquares<pcl::PointXYZRGB, pcl::PointXYZRGBNormal> mls;
+
+	mls.setComputeNormals (true);
+
+	// Set parameters
+	mls.setInputCloud (cloud);
+	mls.setPolynomialFit (smoothingPolynomialFit);
+	mls.setSearchMethod (tree);
+	mls.setSearchRadius (smoothingSearchRadius);
+
+	// Reconstruct
+	mls.process (*cloud_with_normals);
+
+	return cloud_with_normals;
+}
+
+}
+
+}