WebSVN – seema-scanner – Diff – /src/SMReconstructionWorker.cpp


#include "SMReconstructionWorker.h"
 
#include "AlgorithmGrayCode.h"
#include "AlgorithmGrayCodeHorzVert.h"
#include "AlgorithmPhaseShiftTwoFreq.h"
#include "AlgorithmPhaseShiftTwoFreqHorzVert.h"
#include "AlgorithmPhaseShiftThreeFreq.h"
#include "AlgorithmPhaseShiftEmbedded.h"
#include "AlgorithmLineShift.h"
 
#include <QCoreApplication>
#include <QSettings>
 
#include <iostream>
#include <opencv2/opencv.hpp>
 
#include "cvtools.h"
#include <opencv2/core/eigen.hpp>
 
#include <pcl/filters/statistical_outlier_removal.h>
#include <pcl/io/pcd_io.h>
#include <pcl/features/normal_3d.h>
#include <pcl/features/normal_3d_omp.h>
#include <pcl/common/transforms.h>
 
 
 
 
 
void SMReconstructionWorker::reconstructPointCloud(const SMFrameSequence &frameSequence){
 
    QSettings settings;
 
    // Get current calibration
    calibration = settings.value("calibration/parameters").value<SMCalibrationParameters>();
 
    // Create Algorithm
    QString codec = frameSequence.codec;
    int resX = settings.value("projector/resX").toInt();
    int resY = settings.value("projector/resY").toInt();
 
    if(codec == "GrayCode")
        algorithm = new AlgorithmGrayCode(resX, resY);
    else if(codec == "GrayCodeHorzVert")
        algorithm = new AlgorithmGrayCodeHorzVert(resX, resY);
    else if(codec == "PhaseShiftTwoFreq")
        algorithm = new AlgorithmPhaseShiftTwoFreq(resX, resY);
    else if(codec == "PhaseShiftTwoFreqHorzVert")
        algorithm = new AlgorithmPhaseShiftTwoFreqHorzVert(resX, resY);
    else if(codec == "PhaseShiftThreeFreq")
        algorithm = new AlgorithmPhaseShiftThreeFreq(resX, resY);
    else if(codec == "PhaseShiftEmbedded")
        algorithm = new AlgorithmPhaseShiftEmbedded(resX, resY);
    else if(codec == "LineShift")
        algorithm = new AlgorithmLineShift(resX, resY);
    else{
        std::cerr << "SLScanWorker: invalid codec (Please set codec in preferences): " << codec.toStdString() << std::endl;
        return; // otherwise segfault TODO no default?
    }
 
    assert(frameSequence.frames0.size() == algorithm->getNPatterns());
    assert(frameSequence.frames1.size() == algorithm->getNPatterns());
 
    time.start();
 
    // Get 3D Points
    std::vector<cv::Point3f> Q;
    std::vector<cv::Vec3b> color;
    algorithm->get3DPoints(calibration, frameSequence.frames0, frameSequence.frames1, Q, color);
 
    // Convert point cloud to PCL format
    pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr pointCloudPCL(new pcl::PointCloud<pcl::PointXYZRGBNormal>);
 
    pointCloudPCL->width = Q.size();
    pointCloudPCL->height = 1;
    pointCloudPCL->is_dense = true;
 
    pointCloudPCL->points.resize(Q.size());
 
    for(unsigned int i=0; i<Q.size(); i++){
        pcl::PointXYZRGBNormal point;
        point.x = Q[i].x; point.y = Q[i].y; point.z = Q[i].z;
        point.r = color[i][0]; point.g = color[i][1]; point.b = color[i][2];
        pointCloudPCL->points[i] = point;
    }
 
    // Transform point cloud to rotation axis coordinate system
    /*cv::Mat TRCV(3, 4, CV_32F);
    cv::Mat(calibration.Rr).copyTo(TRCV.colRange(0, 3));
    cv::Mat(calibration.Tr).copyTo(TRCV.col(3));
    Eigen::Affine3f TR;
    cv::cv2eigen(TRCV, TR.matrix());
    pcl::transformPointCloud(*pointCloudPCL, *pointCloudPCL, TR);
 
    // Estimate surface normals (does not produce proper normals...)
    std::cout << "Estimating normals..." << std::endl;
    pcl::PointCloud<pcl::PointXYZ>::Ptr points(new pcl::PointCloud<pcl::PointXYZ>);
    pcl::copyPointCloud(*pointCloudPCL, *points);
    pcl::PointCloud<pcl::Normal>::Ptr normals(new pcl::PointCloud<pcl::Normal>);
    pcl::NormalEstimationOMP<pcl::PointXYZ, pcl::Normal> ne;
    pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>());
    tree->setInputCloud(points);
    ne.setSearchMethod(tree);
    ne.setRadiusSearch(1.0);
    //ne.setKSearch(50);
    ne.setViewPoint(0.0, 0.0, 0.0);
    ne.setInputCloud(points);
    ne.compute(*normals);
    pcl::copyPointCloud(*normals, *pointCloudPCL);*/
 
    // Assemble SMPointCloud data structure
    SMPointCloud smPointCloud;
    smPointCloud.id = frameSequence.id;
    smPointCloud.pointCloud = pointCloudPCL;
    smPointCloud.rotationAngle = frameSequence.rotationAngle;
 
    // Determine transform in world (camera0) coordinate system
    float angleRadians = frameSequence.rotationAngle/180.0*M_PI;
    cv::Vec3f rot_rvec(0.0, -angleRadians, 0.0);
    cv::Mat R;
    cv::Rodrigues(rot_rvec, R);
    smPointCloud.R = calibration.Rr.t()*cv::Matx33f(R)*calibration.Rr;
    smPointCloud.T = calibration.Rr.t()*cv::Matx33f(R)*calibration.Tr - calibration.Rr.t()*calibration.Tr;
 
 
    // Determine transform in world (camera0) coordinate system
    /*float angleRadians = frameSequence.rotationAngle/180.0*M_PI;
    cv::Vec3f rot_rvec(0.0, -angleRadians, 0.0);
    cv::Mat R;
    cv::Rodrigues(rot_rvec, R);
    smPointCloud.R = cv::Matx33f(R);
    smPointCloud.T = cv::Vec3f(0.0,0.0,0.0);*/
 
    // Emit result
 
 
    emit newPointCloud(smPointCloud);
    std::cout << "SMReconstructionWorker: " << time.elapsed() << "ms" << std::endl;
    std::cout << "SMReconstructionWorker: " << smPointCloud.pointCloud->size() << " Points" << std::endl;
 
}
 
void SMReconstructionWorker::reconstructPointClouds(const std::vector<SMFrameSequence> &frameSequences){
 
    // Process sequentially
    #pragma omp parallel for
    for(unsigned int i=0; i<frameSequences.size(); i++){
        if(!frameSequences[i].reconstructed) reconstructPointCloud(frameSequences[i]);
    }
}
 
void SMReconstructionWorker::triangulate(const std::vector<cv::Point2f>& q0, const std::vector<cv::Point2f>& q1, std::vector<cv::Point3f> &Q){
    cv::Mat P0(3,4,CV_32F,cv::Scalar(0.0));
    cv::Mat(calibration.K0).copyTo(P0(cv::Range(0,3), cv::Range(0,3)));
 
    cv::Mat temp(3,4,CV_32F);
    cv::Mat(calibration.R1).copyTo(temp(cv::Range(0,3), cv::Range(0,3)));
    cv::Mat(calibration.T1).copyTo(temp(cv::Range(0,3), cv::Range(3,4)));
    cv::Mat P1 = cv::Mat(calibration.K1) * temp;
 
    cv::Mat QMatHomogenous, QMat;
    cv::triangulatePoints(P0, P1, q0, q1, QMatHomogenous);
    cvtools::convertMatFromHomogeneous(QMatHomogenous, QMat);
    cvtools::matToPoints3f(QMat, Q);
}
 

Subversion Repositories seema-scanner

(root)/src/SMReconstructionWorker.cpp – Rev 208 → 225

Rev 208		Rev 225
1	`#include "SMReconstructionWorker.h"`	1	`#include "SMReconstructionWorker.h"`
2		2
3	`#include "AlgorithmGrayCode.h"`	3	`#include "AlgorithmGrayCode.h"`
4	`#include "AlgorithmGrayCodeHorzVert.h"`	4	`#include "AlgorithmGrayCodeHorzVert.h"`
5	`#include "AlgorithmPhaseShiftTwoFreq.h"`	5	`#include "AlgorithmPhaseShiftTwoFreq.h"`
6	`#include "AlgorithmPhaseShiftTwoFreqHorzVert.h"`	6	`#include "AlgorithmPhaseShiftTwoFreqHorzVert.h"`
7	`#include "AlgorithmPhaseShiftThreeFreq.h"`	7	`#include "AlgorithmPhaseShiftThreeFreq.h"`
8	`#include "AlgorithmPhaseShiftEmbedded.h"`	8	`#include "AlgorithmPhaseShiftEmbedded.h"`
9	`#include "AlgorithmLineShift.h"`	9	`#include "AlgorithmLineShift.h"`
10		10
11	`#include <QCoreApplication>`	11	`#include <QCoreApplication>`
12	`#include <QSettings>`	12	`#include <QSettings>`
13		13
14	`#include <iostream>`	14	`#include <iostream>`
15	`#include <opencv2/opencv.hpp>`	15	`#include <opencv2/opencv.hpp>`
16		16
17	`#include "cvtools.h"`	17	`#include "cvtools.h"`
18	`#include <opencv2/core/eigen.hpp>`	18	`#include <opencv2/core/eigen.hpp>`
19		19
20	`#include <pcl/filters/statistical_outlier_removal.h>`	20	`#include <pcl/filters/statistical_outlier_removal.h>`
21	`#include <pcl/io/pcd_io.h>`	21	`#include <pcl/io/pcd_io.h>`
22	`#include <pcl/features/normal_3d.h>`	22	`#include <pcl/features/normal_3d.h>`
23	`#include <pcl/features/normal_3d_omp.h>`	23	`#include <pcl/features/normal_3d_omp.h>`
24	`#include <pcl/common/transforms.h>`	24	`#include <pcl/common/transforms.h>`
25		25
26		26
27	`void SMReconstructionWorker::setup(){`	-
28	`}`	-
29		-
30	`void SMReconstructionWorker::reconstructPointCloud(const SMFrameSequence &frameSequence){`	27	`void SMReconstructionWorker::reconstructPointCloud(const SMFrameSequence &frameSequence){`
31		28
32	`QSettings settings;`	29	`QSettings settings;`
33		30
34	`// Get current calibration`	31	`// Get current calibration`
35	`calibration = settings.value("calibration/parameters").value<SMCalibrationParameters>();`	32	`calibration = settings.value("calibration/parameters").value<SMCalibrationParameters>();`
36		33
37	`// Create Algorithm`	34	`// Create Algorithm`
38	`QString codec = frameSequence.codec;`	35	`QString codec = frameSequence.codec;`
39	`int resX = settings.value("projector/resX").toInt();`	36	`int resX = settings.value("projector/resX").toInt();`
40	`int resY = settings.value("projector/resY").toInt();`	37	`int resY = settings.value("projector/resY").toInt();`
41		38
42	`if(codec == "GrayCode")`	39	`if(codec == "GrayCode")`
43	`algorithm = new AlgorithmGrayCode(resX, resY);`	40	`algorithm = new AlgorithmGrayCode(resX, resY);`
44	`else if(codec == "GrayCodeHorzVert")`	41	`else if(codec == "GrayCodeHorzVert")`
45	`algorithm = new AlgorithmGrayCodeHorzVert(resX, resY);`	42	`algorithm = new AlgorithmGrayCodeHorzVert(resX, resY);`
46	`else if(codec == "PhaseShiftTwoFreq")`	43	`else if(codec == "PhaseShiftTwoFreq")`
47	`algorithm = new AlgorithmPhaseShiftTwoFreq(resX, resY);`	44	`algorithm = new AlgorithmPhaseShiftTwoFreq(resX, resY);`
48	`else if(codec == "PhaseShiftTwoFreqHorzVert")`	45	`else if(codec == "PhaseShiftTwoFreqHorzVert")`
49	`algorithm = new AlgorithmPhaseShiftTwoFreqHorzVert(resX, resY);`	46	`algorithm = new AlgorithmPhaseShiftTwoFreqHorzVert(resX, resY);`
50	`else if(codec == "PhaseShiftThreeFreq")`	47	`else if(codec == "PhaseShiftThreeFreq")`
51	`algorithm = new AlgorithmPhaseShiftThreeFreq(resX, resY);`	48	`algorithm = new AlgorithmPhaseShiftThreeFreq(resX, resY);`
52	`else if(codec == "PhaseShiftEmbedded")`	49	`else if(codec == "PhaseShiftEmbedded")`
53	`algorithm = new AlgorithmPhaseShiftEmbedded(resX, resY);`	50	`algorithm = new AlgorithmPhaseShiftEmbedded(resX, resY);`
54	`else if(codec == "LineShift")`	51	`else if(codec == "LineShift")`
55	`algorithm = new AlgorithmLineShift(resX, resY);`	52	`algorithm = new AlgorithmLineShift(resX, resY);`
56	`else{`	53	`else{`
57	`std::cerr << "SLScanWorker: invalid codec (Please set codec in preferences): " << codec.toStdString() << std::endl;`	54	`std::cerr << "SLScanWorker: invalid codec (Please set codec in preferences): " << codec.toStdString() << std::endl;`
58	`return; // otherwise segfault TODO no default?`	55	`return; // otherwise segfault TODO no default?`
59	`}`	56	`}`
60		57
-		58	`assert(frameSequence.frames0.size() == algorithm->getNPatterns());`
-		59	`assert(frameSequence.frames1.size() == algorithm->getNPatterns());`
-		60
61	`time.start();`	61	`time.start();`
62		62
63	`// Get 3D Points`	63	`// Get 3D Points`
64	`std::vector<cv::Point3f> Q;`	64	`std::vector<cv::Point3f> Q;`
65	`std::vector<cv::Vec3b> color;`	65	`std::vector<cv::Vec3b> color;`
66	`algorithm->get3DPoints(calibration, frameSequence.frames0, frameSequence.frames1, Q, color);`	66	`algorithm->get3DPoints(calibration, frameSequence.frames0, frameSequence.frames1, Q, color);`
67		67
68	`// Convert point cloud to PCL format`	68	`// Convert point cloud to PCL format`
69	`pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr pointCloudPCL(new pcl::PointCloud<pcl::PointXYZRGBNormal>);`	69	`pcl::PointCloud<pcl::PointXYZRGBNormal>::Ptr pointCloudPCL(new pcl::PointCloud<pcl::PointXYZRGBNormal>);`
70		70
71	`pointCloudPCL->width = Q.size();`	71	`pointCloudPCL->width = Q.size();`
72	`pointCloudPCL->height = 1;`	72	`pointCloudPCL->height = 1;`
73	`pointCloudPCL->is_dense = true;`	73	`pointCloudPCL->is_dense = true;`
74		74
75	`pointCloudPCL->points.resize(Q.size());`	75	`pointCloudPCL->points.resize(Q.size());`
76		76
77	`for(unsigned int i=0; i<Q.size(); i++){`	77	`for(unsigned int i=0; i<Q.size(); i++){`
78	`pcl::PointXYZRGBNormal point;`	78	`pcl::PointXYZRGBNormal point;`
79	`point.x = Q[i].x; point.y = Q[i].y; point.z = Q[i].z;`	79	`point.x = Q[i].x; point.y = Q[i].y; point.z = Q[i].z;`
80	`point.r = color[i][0]; point.g = color[i][1]; point.b = color[i][2];`	80	`point.r = color[i][0]; point.g = color[i][1]; point.b = color[i][2];`
81	`pointCloudPCL->points[i] = point;`	81	`pointCloudPCL->points[i] = point;`
82	`}`	82	`}`
83		83
84	`// Transform point cloud to rotation axis coordinate system`	84	`// Transform point cloud to rotation axis coordinate system`
85	`/*cv::Mat TRCV(3, 4, CV_32F);`	85	`/*cv::Mat TRCV(3, 4, CV_32F);`
86	`cv::Mat(calibration.Rr).copyTo(TRCV.colRange(0, 3));`	86	`cv::Mat(calibration.Rr).copyTo(TRCV.colRange(0, 3));`
87	`cv::Mat(calibration.Tr).copyTo(TRCV.col(3));`	87	`cv::Mat(calibration.Tr).copyTo(TRCV.col(3));`
88	`Eigen::Affine3f TR;`	88	`Eigen::Affine3f TR;`
89	`cv::cv2eigen(TRCV, TR.matrix());`	89	`cv::cv2eigen(TRCV, TR.matrix());`
90	`pcl::transformPointCloud(pointCloudPCL, pointCloudPCL, TR);`	90	`pcl::transformPointCloud(pointCloudPCL, pointCloudPCL, TR);`
91		91
92	`// Estimate surface normals (does not produce proper normals...)`	92	`// Estimate surface normals (does not produce proper normals...)`
93	`std::cout << "Estimating normals..." << std::endl;`	93	`std::cout << "Estimating normals..." << std::endl;`
94	`pcl::PointCloud<pcl::PointXYZ>::Ptr points(new pcl::PointCloud<pcl::PointXYZ>);`	94	`pcl::PointCloud<pcl::PointXYZ>::Ptr points(new pcl::PointCloud<pcl::PointXYZ>);`
95	`pcl::copyPointCloud(pointCloudPCL, points);`	95	`pcl::copyPointCloud(pointCloudPCL, points);`
96	`pcl::PointCloud<pcl::Normal>::Ptr normals(new pcl::PointCloud<pcl::Normal>);`	96	`pcl::PointCloud<pcl::Normal>::Ptr normals(new pcl::PointCloud<pcl::Normal>);`
97	`pcl::NormalEstimationOMP<pcl::PointXYZ, pcl::Normal> ne;`	97	`pcl::NormalEstimationOMP<pcl::PointXYZ, pcl::Normal> ne;`
98	`pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>());`	98	`pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>());`
99	`tree->setInputCloud(points);`	99	`tree->setInputCloud(points);`
100	`ne.setSearchMethod(tree);`	100	`ne.setSearchMethod(tree);`
101	`ne.setRadiusSearch(1.0);`	101	`ne.setRadiusSearch(1.0);`
102	`//ne.setKSearch(50);`	102	`//ne.setKSearch(50);`
103	`ne.setViewPoint(0.0, 0.0, 0.0);`	103	`ne.setViewPoint(0.0, 0.0, 0.0);`
104	`ne.setInputCloud(points);`	104	`ne.setInputCloud(points);`
105	`ne.compute(*normals);`	105	`ne.compute(*normals);`
106	`pcl::copyPointCloud(normals, pointCloudPCL);*/`	106	`pcl::copyPointCloud(normals, pointCloudPCL);*/`
107		107
108	`// Assemble SMPointCloud data structure`	108	`// Assemble SMPointCloud data structure`
109	`SMPointCloud smPointCloud;`	109	`SMPointCloud smPointCloud;`
110	`smPointCloud.id = frameSequence.id;`	110	`smPointCloud.id = frameSequence.id;`
111	`smPointCloud.pointCloud = pointCloudPCL;`	111	`smPointCloud.pointCloud = pointCloudPCL;`
112	`smPointCloud.rotationAngle = frameSequence.rotationAngle;`	112	`smPointCloud.rotationAngle = frameSequence.rotationAngle;`
113		113
114	`// Determine transform in world (camera0) coordinate system`	114	`// Determine transform in world (camera0) coordinate system`
115	`float angleRadians = frameSequence.rotationAngle/180.0*M_PI;`	115	`float angleRadians = frameSequence.rotationAngle/180.0*M_PI;`
116	`cv::Vec3f rot_rvec(0.0, -angleRadians, 0.0);`	116	`cv::Vec3f rot_rvec(0.0, -angleRadians, 0.0);`
117	`cv::Mat R;`	117	`cv::Mat R;`
118	`cv::Rodrigues(rot_rvec, R);`	118	`cv::Rodrigues(rot_rvec, R);`
119	`smPointCloud.R = calibration.Rr.t()cv::Matx33f(R)calibration.Rr;`	119	`smPointCloud.R = calibration.Rr.t()cv::Matx33f(R)calibration.Rr;`
120	`smPointCloud.T = calibration.Rr.t()cv::Matx33f(R)calibration.Tr - calibration.Rr.t()*calibration.Tr;`	120	`smPointCloud.T = calibration.Rr.t()cv::Matx33f(R)calibration.Tr - calibration.Rr.t()*calibration.Tr;`
121		121
122		122
123	`// Determine transform in world (camera0) coordinate system`	123	`// Determine transform in world (camera0) coordinate system`
124	`/float angleRadians = frameSequence.rotationAngle/180.0M_PI;`	124	`/float angleRadians = frameSequence.rotationAngle/180.0M_PI;`
125	`cv::Vec3f rot_rvec(0.0, -angleRadians, 0.0);`	125	`cv::Vec3f rot_rvec(0.0, -angleRadians, 0.0);`
126	`cv::Mat R;`	126	`cv::Mat R;`
127	`cv::Rodrigues(rot_rvec, R);`	127	`cv::Rodrigues(rot_rvec, R);`
128	`smPointCloud.R = cv::Matx33f(R);`	128	`smPointCloud.R = cv::Matx33f(R);`
129	`smPointCloud.T = cv::Vec3f(0.0,0.0,0.0);*/`	129	`smPointCloud.T = cv::Vec3f(0.0,0.0,0.0);*/`
130		130
131	`// Emit result`	131	`// Emit result`
132	`#pragma omp critical (CBRECOupdateUI1)`	-
133	`{`	-
134	`emit newPointCloud(smPointCloud);`	132	`emit newPointCloud(smPointCloud);`
135	`std::cout << "SMReconstructionWorker: " << time.elapsed() << "ms" << std::endl;`	133	`std::cout << "SMReconstructionWorker: " << time.elapsed() << "ms" << std::endl;`
136	`std::cout << "SMReconstructionWorker: " << smPointCloud.pointCloud->size() << " Points" << std::endl;`	134	`std::cout << "SMReconstructionWorker: " << smPointCloud.pointCloud->size() << " Points" << std::endl;`
137	`}`	135
138	`}`	136	`}`
139		137
140	`void SMReconstructionWorker::reconstructPointClouds(const std::vector<SMFrameSequence> &frameSequences){`	138	`void SMReconstructionWorker::reconstructPointClouds(const std::vector<SMFrameSequence> &frameSequences){`
-		139
141	`// Process sequentially`	140	`// Process sequentially`
142	`#pragma omp parallel for`	141	`#pragma omp parallel for`
143	`for(unsigned int i=0; i<frameSequences.size(); i++){`	142	`for(unsigned int i=0; i<frameSequences.size(); i++){`
144	`if(!frameSequences[i].reconstructed) reconstructPointCloud(frameSequences[i]);`	143	`if(!frameSequences[i].reconstructed) reconstructPointCloud(frameSequences[i]);`
145	`}`	144	`}`
146	`}`	145	`}`
147		146
148	`void SMReconstructionWorker::triangulate(const std::vector<cv::Point2f>& q0, const std::vector<cv::Point2f>& q1, std::vector<cv::Point3f> &Q){`	147	`void SMReconstructionWorker::triangulate(const std::vector<cv::Point2f>& q0, const std::vector<cv::Point2f>& q1, std::vector<cv::Point3f> &Q){`
149	`cv::Mat P0(3,4,CV_32F,cv::Scalar(0.0));`	148	`cv::Mat P0(3,4,CV_32F,cv::Scalar(0.0));`
150	`cv::Mat(calibration.K0).copyTo(P0(cv::Range(0,3), cv::Range(0,3)));`	149	`cv::Mat(calibration.K0).copyTo(P0(cv::Range(0,3), cv::Range(0,3)));`
151		150
152	`cv::Mat temp(3,4,CV_32F);`	151	`cv::Mat temp(3,4,CV_32F);`
153	`cv::Mat(calibration.R1).copyTo(temp(cv::Range(0,3), cv::Range(0,3)));`	152	`cv::Mat(calibration.R1).copyTo(temp(cv::Range(0,3), cv::Range(0,3)));`
154	`cv::Mat(calibration.T1).copyTo(temp(cv::Range(0,3), cv::Range(3,4)));`	153	`cv::Mat(calibration.T1).copyTo(temp(cv::Range(0,3), cv::Range(3,4)));`
155	`cv::Mat P1 = cv::Mat(calibration.K1) * temp;`	154	`cv::Mat P1 = cv::Mat(calibration.K1) * temp;`
156		155
157	`cv::Mat QMatHomogenous, QMat;`	156	`cv::Mat QMatHomogenous, QMat;`
158	`cv::triangulatePoints(P0, P1, q0, q1, QMatHomogenous);`	157	`cv::triangulatePoints(P0, P1, q0, q1, QMatHomogenous);`
159	`cvtools::convertMatFromHomogeneous(QMatHomogenous, QMat);`	158	`cvtools::convertMatFromHomogeneous(QMatHomogenous, QMat);`
160	`cvtools::matToPoints3f(QMat, Q);`	159	`cvtools::matToPoints3f(QMat, Q);`
161	`}`	160	`}`
162		161