三维重建PCL：点云单侧面正射投影

终于把点云单侧面投影正射投影的代码写完了，为一个阶段，主要使用平面插值方法，且只以XOY平面作为的正射投影面。有些凑合的地方，待改进。

方法思路：使用Mesh模型，对每一个表面进行表面重建。借助OpenCV Mat类型对投影平面进行内点判断，对内点位置进行插值。

OpenCV cv::polylines 和lines 进行画图的时候都会出现问题，因此在某些时刻无法使用连通域查找的方法进行内点检测，应该重写line方法。

1.使用Mesh载入ply模型，和同步载入点云，也可以从mesh直接Copy点云。

     pcl::PolygonMesh cloudMesh;pcl::io::loadPolygonFileOBJ(ViewPath, cloudMesh);pcl::fromPCLPointCloud2(cloudMesh.cloud, *cloud);ViewPath = "D:/DataSet/RGB_data/teapot.pcd";pcl::io::savePCDFileASCII(ViewPath, *cloud);//一定要注意高和宽进行赋值pcl::visualization::PCLVisualizer  Viewer;//pcl::visualization::PCLVisualizer  ViewerMesh;Viewer.addPolygonMesh(cloudMesh);int FrameX = 1000;int FrameY = 1000;int FrameZ = 1000;int Centroid = 0;int num = 12;float gap = 3.141592653/num;Eigen::Vector4f  ViewPoint( 0.0, 0.0, 0.0, 1);//使用弧度ViewPoint[0] = gap*i;cv::Mat imgGray = viewEx->getCloudViewByEdge(cloud, cloudView, cloudMesh, ViewPath, FrameX, FrameY, FrameZ, Centroid, ViewPoint);

2. 使用平面填充方法进行投影...

//使用多边形填充的方法进行投影
//获取点云侧面投影
//输入：点云的点集、边集
cv::Mat CViewExtract::getCloudViewByEdge(pcl::PointCloud<pcl::PointXYZ>::Ptr  cloud,pcl::PointCloud<pcl::PointXYZ>::Ptr  cloudView,pcl::PolygonMesh  &cloudMesh,std::string ViewPath,int FrameX, int FrameY, int FrameZ,int Centroid,Eigen::Vector4f  &ViewPoint)
{int BbxSize = FrameX;pcl::PointCloud<pcl::PointXYZ>::Ptr  cloudTrans(new pcl::PointCloud<pcl::PointXYZ>);this->viewTrans(cloud, cloudTrans, ViewPoint);//对点云进行侧面投影std::vector<pcl::PointCloud<pcl::PointXYZ>> surfaces;pcl::PointCloud<pcl::PointXYZ>::Ptr  surface(new pcl::PointCloud<pcl::PointXYZ>);//计算平面genSurfaceFromVertices(cloudMesh.polygons, cloudTrans, surface);//由cloud替换cloudtrans，mesh只是一个索引cv::Mat imgGray = getViewer(surface, cloudTrans, cloudView);return imgGray;
}

3. 子函数

视点变换

float CViewExtract::viewTrans(pcl::PointCloud<pcl::PointXYZ>::Ptr  cloudSrc,pcl::PointCloud<pcl::PointXYZ>::Ptr  cloudTrans,Eigen::Vector4f  &AngleTrans)
{//1. Trans the VIew...float AngleA, AngleB, AngleC;//声明视角//初始化 作为原始角度AngleA = AngleTrans[0];//49.0/pi;AngleB = AngleTrans[1];//78.9/pi;AngleC = AngleTrans[2];//34.8/pi;int size = cloudSrc->points.size();cloudTrans->resize(0);cloudTrans->reserve(size);//位姿识别角度变换矩阵/Eigen::Matrix4f TransX, TransY, TransZ;//初始化三个矩阵！变换！TransX << 1, 0, 0, 0,0, cos(AngleA), -sin(AngleA), 0,0, sin(AngleA), cos(AngleA), 0,0, 0, 0, 1;//TransY << cos(AngleB), 0, sin(AngleB), 0,0, 1, 0, 0,-sin(AngleB), 0, cos(AngleB), 0,0, 0, 0, 1;TransZ << cos(AngleC), -sin(AngleC), 0, 0,sin(AngleC), cos(AngleC), 0, 0,0, 0, 1, 0,0, 0, 0, 1;//点云模型角度变换Eigen::Vector4f Centroid;Centroid << 0, 0, 0, 0;//pcl::compute3DCentroid(*cloudSrc, Centroid);for (int idx = 0; idx < cloudSrc->points.size(); ++idx){Eigen::Vector4f PointSrc, PointDest;//维数一致！PointSrc[0] = cloudSrc->points[idx].x - Centroid[0];PointSrc[1] = cloudSrc->points[idx].y - Centroid[1];PointSrc[2] = cloudSrc->points[idx].z - Centroid[2];//PointSrc[3] = 1;PointDest = (TransX*(TransY*(TransZ*PointSrc)));//创建矩阵无效！//cloudSrc->points[idx].x = PointDest[0] + Centroid[0];//cloudSrc->points[idx].y = PointDest[1] + Centroid[1];//cloudSrc->points[idx].z = PointDest[2] + Centroid[2];//cloudSrc->points[idx].rgb = cloudSrc->points[idx].rgb;pcl::PointXYZ p;p.x = PointDest[0] + Centroid[0];p.y = PointDest[1] + Centroid[1];p.z = PointDest[2] + Centroid[2];//p.x *= 5; p.y *= 5; p.z *= 5;cloudTrans->push_back(p);//cloudTrans->points[idx].rgb = cloudSrc->points[idx].rgb;}return 1.0;
}

重建表面

//仍然产生整数的空隙，应该把原始点云扩充到四个整数邻域//前N个为原始点云
int CViewExtract::genSurfaceFromVertices(std::vector< ::pcl::Vertices>  &vertices,pcl::PointCloud<pcl::PointXYZ>::Ptr  cloud,pcl::PointCloud<pcl::PointXYZ>::Ptr  surfaces)
{int size = vertices.size();for ( int i = 0; i < size; ++i ){pcl::PointCloud<pcl::PointXYZ>::Ptrsurface(new pcl::PointCloud<pcl::PointXYZ>);//(&surfaces[i]);// genSurfaceFromVertices( vertices[i], cloud, surface, i);for ( auto p : surface->points){surfaces->points.push_back(p);}surface->clear();}return size;
}

//从表面获取点云，对单个面获取点云
int CViewExtract::genSurfaceFromVertices(const pcl::Vertices &vertice,const pcl::PointCloud<pcl::PointXYZ>::Ptr  cloud,pcl::PointCloud<pcl::PointXYZ>::Ptr  surface,int idx)
{int size = 0;int nV = vertice.vertices.size();pcl::PointCloud<pcl::PointXYZ>::Ptr Votex(new pcl::PointCloud<pcl::PointXYZ>);for (int i = 0; i < nV; ++i){pcl::PointXYZ p(cloud->points[vertice.vertices[i]]);Votex->points.push_back(p);}int bx, by, bz;std::vector<std::pair<float, float> > minmax(3);//findMinMax( cloud, minmax );MathCal::findMinMax(Votex, minmax);bx = ceil(minmax[0].second - minmax[0].first);by = ceil(minmax[1].second - minmax[1].first);bz = ceil(minmax[2].second - minmax[2].first);//bx *= 10; by *= 10; bz *= 10;//取平面上的点//以Z轴为正射方向std::vector<cv::Point2f> vetexs(0);//生成顶点int xmin = minmax[0].first;int ymin = minmax[1].first;int zmin = minmax[2].first;for (int i = 0; i < vertice.vertices.size(); ++i){int idx = vertice.vertices[i];pcl::PointXYZ p = cloud->points[idx];cv::Point2f p2 = cv::Point2f(p.x - xmin, p.y - ymin);//p2.x *= 10;p2.y *= 10;vetexs.push_back(p2);}//生成图像//使用OpenCV画出对应二维图片cv::Mat img = cv::Mat::zeros(by + 1, bx + 1, CV_8UC3);cv::Mat _lableImg;std::vector<std::vector<cv::Point > > foreAreas;//wishchin::findInliners2d( img, vetexs, _lableImg, foreAreas );MathCal::findInliners2dNoCon(img, vetexs, _lableImg, foreAreas);float zmean = 0;if (foreAreas.size()>0){size = foreAreas[0].size();//获取平面方程//Ax + By + Cz + D//std::vector<float> getPlaneParam(std::vector<cv::Point2f> vetexs);std::vector<pcl::PointXYZ> VotexP;for (int i = 0; i < vetexs.size(); ++i){pcl::PointXYZ p(vetexs[i].x, vetexs[i].y, (cloud->points[vertice.vertices[i]].z - zmin));VotexP.push_back(p);zmean += cloud->points[vertice.vertices[i]].z;}zmean /= vetexs.size();std::vector<float> abcd = MathCal::getPlaneParam(VotexP);//从平面上取点surface->points.resize(0);float x, y, z;//Mat xy的方向与 PCL是相反的！！！for (int i = 0; i < size; ++i){x = foreAreas[0][i].x;y = foreAreas[0][i].y;//x = bx + 0 - x;//y = by + 0 - y;z = 0-(abcd[0] * x + abcd[1] * y + abcd[3]) / abcd[2];pcl::PointXYZ p(x,y, z);p.x += xmin; p.y += ymin; p.z += zmin;//移到原位surface->points.push_back(p);}surface->height = 1;surface->width = size;}return size;
}

寻找多边形的内点

//寻找多边形的内点//取整数点//只能取凸多边形
//通过判断各个边的左边右边来进行计算//通过计算在多边形的内侧外侧计算-有点慢
//不使用连通域查找//
int MathCal::findInliners2dNoCon(cv::Mat &img, std::vector<cv::Point2f> &vetexs,cv::Mat &_lableImg, std::vector<std::vector<cv::Point > > &foreAreas)
{int size = 0;//获取多边形边集std::vector<std::vector<cv::Point2f>>  edges(0);if (vetexs.size() > 2){std::vector<cv::Point2f> edge(0);edge.push_back(cv::Point2f(vetexs[vetexs.size() - 1]));edge.push_back(cv::Point2f(vetexs[0]));edges.push_back(edge);for (int i = 1; i < vetexs.size(); ++i){edge.resize(0);edge.push_back(cv::Point2f(vetexs[i - 1]));edge.push_back(cv::Point2f(vetexs[i]));edges.push_back(edge);}}//测试//bool isIn =isInliner(cv::Point2f(2, 538), vetexs, edges);//true//bool isIn = isInliner(cv::Point2f(476, 258), vetexs, edges);//false//bool isIn = isInliner(cv::Point2f(704, 137), vetexs, edges);//bool isIn = isInliner(cv::Point2f(6, 11), vetexs, edges);//取多边形的质心//从质心开始查找连通域//需要提前染色std::vector<cv::Point2d> inliners;cv::Point2d seed(-1, -1);bool findseed = false;std::vector<cv::Point > foreArea;for (int i = 0; i < img.rows; ++i){unsigned char *ptrm = img.ptr<unsigned char>(i);for (int j = 0; j < img.cols; ++j){int c = *ptrm;bool isIn = false;isIn = isInliner(cv::Point2f(j, i), vetexs, edges); //！！！！！出现错误！待调试！//出现了两个方向都奇异的直角三角形if (isIn){seed.x = j;seed.y = i;foreArea.push_back(seed);}++ptrm;}}if (foreArea.size()>0){foreAreas.push_back(foreArea);}size = foreAreas.size();return size;
}

获取平面方程

//获取平面方程//Ax + By + Cz + D
std::vector<float> MathCal::getPlaneParam(const std::vector<pcl::PointXYZ> &votexs)
{std::vector<float> abcd;if (votexs.size() < 3){return abcd;}else{//取前三个点计算平面float x1, x2, x3, y1, y2, y3, z1, z2, z3;x1 = votexs[0].x; x2 = votexs[1].x; x3 = votexs[2].x;y1 = votexs[0].y; y2 = votexs[1].y; y3 = votexs[2].y;z1 = votexs[0].z; z2 = votexs[1].z; z3 = votexs[2].z;float A = y1*(z2 - z3) + y2*(z3 - z1) + y3*(z1 - z2);float B = z1*(x2 - x3) + z2*(x3 - x1) + z3*(x1 - x2);float C = x1*(y2 - y3) + x2*(y3 - y1) + x3*(y1 - y2);float D = -(x1*(y2*z3 - y3*z2) + x2*(y3*z1 - y1*z3) + x3*(y1*z2 - y2*z1));abcd.push_back(A); abcd.push_back(B); abcd.push_back(C);abcd.push_back(D);}return abcd;
}

int MathCal::findMinMax(pcl::PointCloud<pcl::PointXYZ>::Ptr cloud,std::vector<std::pair<float, float> > &minmax)
{float minX = 10000000;float minY = 10000000;float minZ = 10000000;float maxX = -10000000;float maxY = -10000000;float maxZ = -10000000;for (int i = 0; i < cloud->points.size(); ++i){pcl::PointXYZ p(cloud->points[i]);if (minX >p.x) minX = p.x;if (minY > p.y) minY = p.y;if (minZ > p.z) minZ = p.z;if (maxX < p.x) maxX = p.x;if (maxY < p.y) maxY = p.y;if (maxZ < p.z) maxZ = p.z;}minmax.resize(0);minmax.push_back(std::pair<float, float>(minX, maxX));minmax.push_back(std::pair<float, float>(minY, maxY));minmax.push_back(std::pair<float, float>(minZ, maxZ));return 1;
}

//获取点云，直接从上一步获取
cv::Mat  CViewExtract::getViewer(const pcl::PointCloud<pcl::PointXYZ>::Ptr  surface,const pcl::PointCloud<pcl::PointXYZ>::Ptr  cloud,pcl::PointCloud<pcl::PointXYZ>::Ptr  cloudView)
{//获取大包围盒int bx, by, bz;std::vector<std::pair<float, float> > minmax(3);MathCal::findMinMax(surface, minmax);float xmin = minmax[0].first;float ymin = minmax[1].first;float zmin = minmax[2].first;bx = ceil(minmax[0].second - minmax[0].first);by = ceil(minmax[1].second - minmax[1].first);bz = ceil(minmax[2].second - minmax[2].first);std::vector<float> bbx;bbx.push_back(bx); bbx.push_back(by); bbx.push_back(bz);//std::vector<bool > visibies(surface->points.size() );//直接重新生成点，不取浮点数//生成图像//使用OpenCV画出对应灰度图片cv::Mat img = cv::Mat::zeros(by + 1, bx + 1, CV_32FC1);//for ( pcl::PointXYZ p: surface->points )for (int i = 0; i < surface->points.size(); ++i){pcl::PointXYZ p = surface->points[i];int x = p.x - xmin;int y = p.y - ymin;float z = p.z - zmin + 1;//取最大Z//必须使用四邻域int x1 = floor(x); int x2 = ceil(x); //if (x1 < 0) x1 = 0;int y1 = floor(y); int y2 = ceil(y); //if (y1 < 0) y1 = 0;MathCal::cutValue(x1, 0, img.cols - 1);MathCal::cutValue(x2, 0, img.cols - 1);MathCal::cutValue(y1, 0, img.rows - 1);MathCal::cutValue(y2, 0, img.rows - 1);if ( img.at<float>(y1, x1) < z) img.at<float>(y1, x1) = z;if ( img.at<float>(y1, x2) < z) img.at<float>(y1, x2) = z;if ( img.at<float>(y2, x2) < z) img.at<float>(y2, x2) = z;if ( img.at<float>(y2, x1) < z) img.at<float>(y2, x1) = z;}//补加原始点云的四邻域//原始点云已添加，不再重复补偿，原始点云已删除pcl::PointCloud<pcl::PointXYZ>::Ptr  cloudFourNear(new pcl::PointCloud<pcl::PointXYZ>);for (int i = 0; i < cloud->points.size(); ++i){pcl::PointXYZ p = cloud->points[i];float x = p.x - xmin;float y = p.y - ymin;float z = p.z - zmin + 1;int x1 = floor(x); int x2 = ceil(x); //if (x1<0) x1 = 0; if (x2<0) x2 = 0;int y1 = floor(y); int y2 = ceil(y); //if (y1<0) y1 = 0; if (y2<0) y2 = 0;MathCal::cutValue(x1, 0, img.cols - 1);MathCal::cutValue(x2, 0, img.cols - 1);MathCal::cutValue(y1, 0, img.rows - 1);MathCal::cutValue(y2, 0, img.rows - 1);//重复填充四邻域//若未被填充，则填充if ( 0.0001> img.at<float>(y1, x1) ) img.at<float>(y1, x1) = z;if (0.0001> img.at<float>(y1, x2)) img.at<float>(y1, x2) = z;if (0.0001> img.at<float>(y2, x2)) img.at<float>(y2, x2) = z;if (0.0001> img.at<float>(y2, x1)) img.at<float>(y2, x1) = z;}cloudView->resize(0);cv::Mat imgGray = cv::Mat::zeros(by + 1, bx + 1, CV_8UC1);float x, y, z;for (int i = 0; i < img.rows; ++i){float *ptr = img.ptr<float>(i);unsigned char *ptrg = imgGray.ptr<unsigned char>(i);for (int j = 0; j < img.cols; ++j){if (*ptr > 0){x = j - xmin;y = i - ymin;z = *ptr - zmin-1;cloudView->points.push_back(pcl::PointXYZ(x, y, z));if (z < 0) z = 0;if (z >255) z = 255;*ptrg = (unsigned char)z;}++ptr;++ptrg;}}cloudView->height = 1;cloudView->width = cloudView->points.size();//cv::flip(imgGray, imgGray, 2);//cv::imshow("imgGray", imgGray);//cv::waitKey(0);return imgGray;
}

void MathCal::cutValue(int &inv, const int start, const int end)
{if (inv < start) inv = start;if (inv > end) inv = end;//return inv;
}

输出结果；

通过传入viewpoint输出不同的位姿可见面

貌似遗漏的代码：

//检测是否是内点
bool MathCal::isInliner(const cv::Point2f &p, const std::vector<cv::Point2f> &poly,const std::vector<std::vector<cv::Point2f>>  &edges)
{return point_in_polygon_byRay(p, poly, edges);
}

// 应该使用射线方法，用于取代geometry里面的方法
bool MathCal::point_in_polygon_byRay(const  cv::Point2f &p,const std::vector<cv::Point2f> &poly,const std::vector<std::vector<cv::Point2f>> &edges)
{bool isIn = false;// 从点C到任一边的中点引射线float x = (poly[0].x + poly[1].x) / 2;float y = (poly[0].y + poly[1].y) / 2;cv::Point2f co(x, y);float rayvectorx = x - p.x;float rayvectory = y - p.y;cv::Point2f rayV(rayvectorx, rayvectory);// rayx/rayy 为射线的起点std::vector<bool> crosses;// = new ArrayList<Boolean>();cv::Point2f intersectpoint;// = new cv::Point2f();for (int i = 0; i < edges.size(); ++i) {cv::Point2f ps = edges[i][0];cv::Point2f pe = edges[i][1];bool isCross =//intersection_ray_segment_point(p, rayV, ps, pe, intersectpoint);intersection_ray0_segment_point(p, co, ps, pe, intersectpoint);crosses.push_back(isCross);}int numCross = 0;for (bool is : crosses) {if (is) {numCross++;}}if (numCross % 2 == 0) {isIn = false;}elseisIn = true;return isIn;
}

//使用射线方法，判断内点//直接使用点，最后计算射线，反复计算射线出现精度问题！！！！
// 判断射线和线段是否有交点//起始点，方向向量，线段始末点，交点
bool MathCal::intersection_ray0_segment_point(const cv::Point2f &p,cv::Point2f &pe1, cv::Point2f &ps, cv::Point2f &pe,cv::Point2f &intersectpoint) {// 判断线段是否和直线相交cv::Point2f orientVec2(pe.x - ps.x, pe.y - ps.y);cv::Point2f pcross;// = new cv::Point2f();intersection_point_float(p, pe1, ps, pe, pcross);//intersection_point_orient(p, rayV, ps, orientVec2, pcross);// 判断交点是否在线段上bool isin = false;//判断条件有错误！//判断仅限定于x，出现失误//if (pcross.x >= ps.x && pcross.x <= pe.x || pcross.x <= ps.x && pcross.x >= pe.x) {//   isin = true;//}float errorf = 0.00001;float minx = std::min(ps.x, pe.x) - errorf;float maxx = std::max(ps.x, pe.x) + errorf;float miny = std::min(ps.y, pe.y) - errorf;float maxy = std::max(ps.y, pe.y) + errorf;if (pcross.x < maxx &&pcross.x > minx && pcross.y < maxy && pcross.y > miny){isin = true;}// 判断是否在射线方向上//cv::Point2f co(x, y);float rayvectorx = pe1.x - p.x;float rayvectory = pe1.y - p.y;cv::Point2f rayV(rayvectorx, rayvectory);float xDeta = pcross.x - p.x;bool isInVec = false;if (xDeta * rayV.x > 0) {isInVec = true;}isin = isin && isInVec;return isin;
}

float MathCal::intersection_point_float(const  cv::Point2f &ps, cv::Point2f &pe, cv::Point2f &ps2, cv::Point2f &pe2,cv::Point2f &pcross) {float friststartx = ps.x;float friststarty = ps.y;float fristendx = pe.x;float fristendy = pe.y;float secondstartx = ps2.x;float secondstarty = ps2.y;float secondendx = pe2.x;float secondendy = pe2.y;intersection_point_float(friststartx, friststarty, fristendx, fristendy, secondstartx, secondstarty,secondendx, secondendy, pcross);//计算交点出现问题！return 0;
}

bool MathCal::intersection_point_float(float friststartx, float friststarty, float fristendx,float fristendy, float secondstartx, float secondstarty, float secondendx, float secondendy,cv::Point2f &newpt) {//float a1 = (friststarty - fristendy) / (friststartx - fristendx);//float b1 = friststarty - a1 * (friststartx);//float a2 = (secondstarty - secondendy) / (secondstartx - secondendx);//float b2 = secondstarty - a1 * secondstartx;//newpt.x = (b1 - b2) / (a2 - a1);//newpt.y = a1 * newpt.x + b1;double dx1 = fristendx - friststartx;double dx2 = secondendx - secondstartx;double dx3 = friststartx - secondstartx;double dy1 = fristendy - friststarty;double dy2 = friststarty - secondstarty;double dy3 = secondendy - secondstarty;double ratio = dx1 * dy3 - dy1 * dx2;if (ratio != 0.0) //{ratio = (dy2 * dx2 - dx3 * dy3) / ratio;newpt.x = (friststartx + ratio * dx1);newpt.y = (friststarty + ratio * dy1);return true;}return true;
}

此次貌似已经没有问题了。不要在意注释，注释应该是修改后还没有来得及删除。

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