【PCL-8】方向包围盒OBB

 AABB包围盒：边平行于坐标轴的最小六面体；

方向包围盒OBB：相对于坐标轴方向任意的最小立方体。

最小包围盒计算流程：

1、利用PCA主元分析法获得点云的三个主方向，获取质心，计算协方差，得到协方差矩阵，求取协方差矩阵的特征值和特征向量，特征向量即为主方向；

2、根据1获得的主方向和质心，将输入点云转换至原点，且主方向与坐标系方向重合，建立变换到原点的点云包围盒；

3、给输入点云设置主方向和包围盒，通过输入点云到原点点云变换的逆变换实现。

实现代码：

1、直接利用addcube生成立方体。

#include <pcl/features/moment_of_inertia_estimation.h>
#include <pcl/io/pcd_io.h>
#include <pcl/point_types.h>
#include <pcl/visualization/cloud_viewer.h>
#include <pcl/common/transforms.h>


int main(int argc, char** argv)
{
	pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>());
	if (pcl::io::loadPCDFile("..\\testdata\\point0817-3.pcd", *cloud) == -1)
		return (-1);
	//创建惯性矩估算对象，设置输入点云，并进行计算
	pcl::MomentOfInertiaEstimation <pcl::PointXYZ> feature_extractor;
	feature_extractor.setInputCloud(cloud);
	feature_extractor.compute();

	vector <float> moment_of_inertia;
	vector <float> eccentricity;
	//pcl::PointXYZ min_point_AABB;
	//pcl::PointXYZ max_point_AABB;
	pcl::PointXYZ min_point_OBB;
	pcl::PointXYZ max_point_OBB;
	pcl::PointXYZ position_OBB;
	//矩阵特征值、特征向量
	Eigen::Matrix3f rotational_matrix_OBB;
	float major_value, middle_value, minor_value;
	Eigen::Vector3f major_vector, middle_vector, minor_vector;
	Eigen::Vector3f mass_center;
	//获取惯性矩
	feature_extractor.getMomentOfInertia(moment_of_inertia);
	//获取离心率
	feature_extractor.getEccentricity(eccentricity);
	//feature_extractor.getAABB(min_point_AABB, max_point_AABB);
	//获取OBB盒子
	feature_extractor.getOBB(min_point_OBB, max_point_OBB, position_OBB, rotational_matrix_OBB);
	cout << min_point_OBB.x << endl;
	feature_extractor.getEigenValues(major_value, middle_value, minor_value);
	//获取主轴major_vector，中轴middle_vector，辅助轴minor_vector
	feature_extractor.getEigenVectors(major_vector, middle_vector, minor_vector);
	//获取质心
	feature_extractor.getMassCenter(mass_center);

	//AABB外接立方体
	pcl::visualization::PCLVisualizer::Ptr viewer(new pcl::visualization::PCLVisualizer("3D Viewer"));
	viewer->setBackgroundColor(128.0 / 255.0, 138.0 / 255.0, 135.0 / 255.0);
	viewer->addCoordinateSystem(0.1);
	viewer->initCameraParameters();
	viewer->addPointCloud<pcl::PointXYZ>(cloud, "sample cloud");
	//viewer->addCube(min_point_AABB.x, max_point_AABB.x, min_point_AABB.y, max_point_AABB.y, min_point_AABB.z, max_point_AABB.z, 1.0, 0.0, 0.0, "AABB", 0);
	//viewer->setShapeRenderingProperties(pcl::visualization::PCL_VISUALIZER_REPRESENTATION, pcl::visualization::PCL_VISUALIZER_REPRESENTATION_POINTS, "AABB");

	//OBB外接立方体，添加OBB包容盒
	Eigen::Vector3f position(position_OBB.x, position_OBB.y, position_OBB.z);
	Eigen::Quaternionf quat(rotational_matrix_OBB);
	viewer->addCube(position, quat, max_point_OBB.x - min_point_OBB.x, max_point_OBB.y - min_point_OBB.y, max_point_OBB.z - min_point_OBB.z, "OBB");
	viewer->setShapeRenderingProperties(pcl::visualization::PCL_VISUALIZER_REPRESENTATION, pcl::visualization::PCL_VISUALIZER_REPRESENTATION_WIREFRAME, "OBB");
	//最小外接立方体的长、宽、高；quat:旋转矩阵；position:中心位置
	cout << max_point_OBB.x << endl;
	cout << max_point_OBB.y << endl;
	cout << min_point_OBB.x << endl;
	cout << min_point_OBB.y << endl;
	cout << position_OBB.x << endl;
	cout << position_OBB.y << endl;
	cout << position_OBB.z << endl;
	cout << max_point_OBB.x - min_point_OBB.x << endl;
	cout << max_point_OBB.y - min_point_OBB.y << endl;
	cout << max_point_OBB.z - min_point_OBB.z << endl;
	cout << rotational_matrix_OBB << endl;
	//中心点处加坐标
	//pcl::PointXYZ center(mass_center(0), mass_center(1), mass_center(2));
	//pcl::PointXYZ x_axis(major_vector(0) + mass_center(0), major_vector(1) + mass_center(1), major_vector(2) + mass_center(2));
	//pcl::PointXYZ y_axis(middle_vector(0) + mass_center(0), middle_vector(1) + mass_center(1), middle_vector(2) + mass_center(2));
	//pcl::PointXYZ z_axis(minor_vector(0) + mass_center(0), minor_vector(1) + mass_center(1), minor_vector(2) + mass_center(2));


	//viewer->addLine(center, x_axis, 1.0f, 0.0f, 0.0f, "major eigen vector");
	//viewer->addLine(center, y_axis, 0.0f, 1.0f, 0.0f, "middle eigen vector");
	//viewer->addLine(center, z_axis, 0.0f, 0.0f, 1.0f, "minor eigen vector");

	while (!viewer->wasStopped())
	{
		viewer->spinOnce(100);
		boost::this_thread::sleep(boost::posix_time::microseconds(100000));
	}

	return (0);
}

测试效果：

2、获取每个角点坐标，利用addLine划线。

//addLine画线
Eigen::Vector3f p1 (min_point_OBB.x, min_point_OBB.y, min_point_OBB.z);
Eigen::Vector3f p2 (min_point_OBB.x, min_point_OBB.y, max_point_OBB.z);
Eigen::Vector3f p3 (max_point_OBB.x, min_point_OBB.y, max_point_OBB.z);
Eigen::Vector3f p4 (max_point_OBB.x, min_point_OBB.y, min_point_OBB.z);
Eigen::Vector3f p5 (min_point_OBB.x, max_point_OBB.y, min_point_OBB.z);
Eigen::Vector3f p6 (min_point_OBB.x, max_point_OBB.y, max_point_OBB.z);
Eigen::Vector3f p7 (max_point_OBB.x, max_point_OBB.y, max_point_OBB.z);
Eigen::Vector3f p8 (max_point_OBB.x, max_point_OBB.y, min_point_OBB.z);

p1 = rotational_matrix_OBB * p1 + position;
p2 = rotational_matrix_OBB * p2 + position;
p3 = rotational_matrix_OBB * p3 + position;
p4 = rotational_matrix_OBB * p4 + position;
p5 = rotational_matrix_OBB * p5 + position;
p6 = rotational_matrix_OBB * p6 + position;
p7 = rotational_matrix_OBB * p7 + position;
p8 = rotational_matrix_OBB * p8 + position;

pcl::PointXYZ pt1 (p1 (0), p1 (1), p1 (2));
pcl::PointXYZ pt2 (p2 (0), p2 (1), p2 (2));
pcl::PointXYZ pt3 (p3 (0), p3 (1), p3 (2));
pcl::PointXYZ pt4 (p4 (0), p4 (1), p4 (2));
pcl::PointXYZ pt5 (p5 (0), p5 (1), p5 (2));
pcl::PointXYZ pt6 (p6 (0), p6 (1), p6 (2));
pcl::PointXYZ pt7 (p7 (0), p7 (1), p7 (2));
pcl::PointXYZ pt8 (p8 (0), p8 (1), p8 (2));

viewer->addLine (pt1, pt2, 1.0, 0.0, 0.0, "1 edge");
viewer->addLine (pt1, pt4, 1.0, 0.0, 0.0, "2 edge");
viewer->addLine (pt1, pt5, 1.0, 0.0, 0.0, "3 edge");
viewer->addLine (pt5, pt6, 1.0, 0.0, 0.0, "4 edge");
viewer->addLine (pt5, pt8, 1.0, 0.0, 0.0, "5 edge");
viewer->addLine (pt2, pt6, 1.0, 0.0, 0.0, "6 edge");
viewer->addLine (pt6, pt7, 1.0, 0.0, 0.0, "7 edge");
viewer->addLine (pt7, pt8, 1.0, 0.0, 0.0, "8 edge");
viewer->addLine (pt2, pt3, 1.0, 0.0, 0.0, "9 edge");
viewer->addLine (pt4, pt8, 1.0, 0.0, 0.0, "10 edge");
viewer->addLine (pt3, pt4, 1.0, 0.0, 0.0, "11 edge");
viewer->addLine (pt3, pt7, 1.0, 0.0, 0.0, "12 edge");

测试效果：

坐标系：

 点云数据坐标系为右手坐标系，红色是X轴，绿色是Y轴，蓝色是Z轴。

参考链接 pcl_包围盒_基于惯性矩与偏心率的描述子_yamgyutou的博客-CSDN博客

pcl中MomentOfInertiaEstimation计算有向包围盒_pclobb包围盒_chen_jared的博客-CSDN博客

 PCL ——最小包围盒(画出了最小包围盒并求出顶点坐标)_包围盒算法_云初的博客-CSDN博客