Visual SLAM 14 講座 - ch9 の実践操作とピット回避
0. 実践前の豆知識のご紹介
0.1 データセットの使用
Ceres BA は BAL データセットを使用します。この例では、problem-16-22106-pre.txt ファイルを使用します。
BAL データセット自体には特別な機能があります。
BAL のカメラ固有参照モデルは、焦点距離 f と歪みパラメータ k1、k2 によって与えられます。
BAL データは、以前に使用したモデルに従って、投影中に投影面がカメラの光学中心の後ろにあることを前提としているため、投影後に係数 -1 を乗算する必要があります。
1. 実運用前の準備
- 拡張子 .ply が付いた 2 つのファイルが生成されるため、meshlab をインストールします。これら 2 つのファイルは Meshlab で表示する必要があります。
インストールコマンド:
sudo apt-get update
sudo apt-get install meshlab
- ターミナルでch9フォルダに入り、以下のコマンドを実行してコンパイルします。
mkdir build
cd build
cmake ..
//注意，j8还是其他主要看自己的电脑情况
make -j8
- ビルドファイル内で実行します。
注:作成プロセス中に、警告、しかし私たちの練習のプロセスにはほとんど影響しません。
2. 練習プロセス
2.1 セレスBA
コード：
#include <iostream>
#include <ceres/ceres.h>
#include "common.h"
#include "SnavelyReprojectionError.h"
using namespace std;
void SolveBA(BALProblem &bal_problem);
int main(int argc, char **argv) {
if (argc != 2) {
cout << "usage: bundle_adjustment_ceres bal_data.txt" << endl;
return 1;
}
BALProblem bal_problem(argv[1]);
bal_problem.Normalize();
bal_problem.Perturb(0.1, 0.5, 0.5);
bal_problem.WriteToPLYFile("initial.ply");
SolveBA(bal_problem);
bal_problem.WriteToPLYFile("final.ply");
return 0;
}
void SolveBA(BALProblem &bal_problem) {
const int point_block_size = bal_problem.point_block_size();
const int camera_block_size = bal_problem.camera_block_size();
double *points = bal_problem.mutable_points();
double *cameras = bal_problem.mutable_cameras();
// Observations is 2 * num_observations long array observations
// [u_1, u_2, ... u_n], where each u_i is two dimensional, the x
// and y position of the observation.
const double *observations = bal_problem.observations();
ceres::Problem problem;
for (int i = 0; i < bal_problem.num_observations(); ++i) {
ceres::CostFunction *cost_function;
// Each Residual block takes a point and a camera as input
// and outputs a 2 dimensional Residual
cost_function = SnavelyReprojectionError::Create(observations[2 * i + 0], observations[2 * i + 1]);
// If enabled use Huber's loss function.
ceres::LossFunction *loss_function = new ceres::HuberLoss(1.0);
// Each observation corresponds to a pair of a camera and a point
// which are identified by camera_index()[i] and point_index()[i]
// respectively.
double *camera = cameras + camera_block_size * bal_problem.camera_index()[i];
double *point = points + point_block_size * bal_problem.point_index()[i];
problem.AddResidualBlock(cost_function, loss_function, camera, point);
}
// show some information here ...
std::cout << "bal problem file loaded..." << std::endl;
std::cout << "bal problem have " << bal_problem.num_cameras() << " cameras and "
<< bal_problem.num_points() << " points. " << std::endl;
std::cout << "Forming " << bal_problem.num_observations() << " observations. " << std::endl;
std::cout << "Solving ceres BA ... " << endl;
ceres::Solver::Options options;
options.linear_solver_type = ceres::LinearSolverType::SPARSE_SCHUR;
options.minimizer_progress_to_stdout = true;
ceres::Solver::Summary summary;
ceres::Solve(options, &problem, &summary);
std::cout << summary.FullReport() << "\n";
}
ビルドでステートメントを実行します。
./bundle_adjustment_ceres /home/fighter/slam/slambook2/ch9/problem-16-22106-pre.txt
操作結果:
Header: 16 22106 83718bal problem file loaded...
bal problem have 16 cameras and 22106 points.
Forming 83718 observations.
Solving ceres BA ...
iter cost cost_change |gradient| |step| tr_ratio tr_radius ls_iter iter_time total_time
0 1.842900e+07 0.00e+00 2.04e+06 0.00e+00 0.00e+00 1.00e+04 0 1.84e-01 6.03e-01
1 1.449093e+06 1.70e+07 1.75e+06 2.16e+03 1.84e+00 3.00e+04 1 2.79e-01 8.82e-01
2 5.848543e+04 1.39e+06 1.30e+06 1.55e+03 1.87e+00 9.00e+04 1 1.37e-01 1.02e+00
3 1.581483e+04 4.27e+04 4.98e+05 4.98e+02 1.29e+00 2.70e+05 1 1.28e-01 1.15e+00
4 1.251823e+04 3.30e+03 4.64e+04 9.96e+01 1.11e+00 8.10e+05 1 1.24e-01 1.27e+00
5 1.240936e+04 1.09e+02 9.78e+03 1.33e+01 1.42e+00 2.43e+06 1 1.27e-01 1.40e+00
6 1.237699e+04 3.24e+01 3.91e+03 5.04e+00 1.70e+00 7.29e+06 1 1.29e-01 1.53e+00
7 1.236187e+04 1.51e+01 1.96e+03 3.40e+00 1.75e+00 2.19e+07 1 1.26e-01 1.65e+00
8 1.235405e+04 7.82e+00 1.03e+03 2.40e+00 1.76e+00 6.56e+07 1 1.24e-01 1.78e+00
9 1.234934e+04 4.71e+00 5.04e+02 1.67e+00 1.87e+00 1.97e+08 1 1.26e-01 1.90e+00
10 1.234610e+04 3.24e+00 4.31e+02 1.15e+00 1.88e+00 5.90e+08 1 1.29e-01 2.03e+00
11 1.234386e+04 2.24e+00 3.27e+02 8.44e-01 1.90e+00 1.77e+09 1 1.28e-01 2.16e+00
12 1.234232e+04 1.54e+00 3.44e+02 6.69e-01 1.82e+00 5.31e+09 1 1.26e-01 2.29e+00
13 1.234126e+04 1.07e+00 2.21e+02 5.45e-01 1.91e+00 1.59e+10 1 1.24e-01 2.41e+00
14 1.234047e+04 7.90e-01 1.12e+02 4.84e-01 1.87e+00 4.78e+10 1 1.25e-01 2.54e+00
15 1.233986e+04 6.07e-01 1.02e+02 4.22e-01 1.95e+00 1.43e+11 1 1.28e-01 2.66e+00
16 1.233934e+04 5.22e-01 1.03e+02 3.82e-01 1.97e+00 4.30e+11 1 1.30e-01 2.79e+00
17 1.233891e+04 4.25e-01 1.07e+02 3.46e-01 1.93e+00 1.29e+12 1 1.22e-01 2.92e+00
18 1.233855e+04 3.59e-01 1.04e+02 3.15e-01 1.96e+00 3.87e+12 1 1.23e-01 3.04e+00
19 1.233825e+04 3.06e-01 9.27e+01 2.88e-01 1.98e+00 1.16e+13 1 1.21e-01 3.16e+00
20 1.233799e+04 2.61e-01 1.17e+02 2.16e-01 1.97e+00 3.49e+13 1 1.22e-01 3.28e+00
21 1.233777e+04 2.18e-01 1.22e+02 1.15e-01 1.97e+00 1.05e+14 1 1.20e-01 3.40e+00
22 1.233760e+04 1.73e-01 1.10e+02 9.59e-02 1.89e+00 3.14e+14 1 1.22e-01 3.53e+00
23 1.233746e+04 1.37e-01 1.14e+02 1.68e-01 1.98e+00 9.41e+14 1 1.24e-01 3.65e+00
24 1.233735e+04 1.13e-01 1.17e+02 2.36e-01 1.96e+00 2.82e+15 1 1.28e-01 3.78e+00
25 1.233725e+04 9.50e-02 1.18e+02 1.28e+00 1.99e+00 8.47e+15 1 1.23e-01 3.90e+00
WARNING: Logging before InitGoogleLogging() is written to STDERR
W0615 16:19:52.003427 5230 levenberg_marquardt_strategy.cc:116] Linear solver failure. Failed to compute a step: CHOLMOD warning: Matrix not positive definite.
26 1.233725e+04 0.00e+00 1.18e+02 0.00e+00 0.00e+00 4.24e+15 1 4.75e-02 3.95e+00
W0615 16:19:52.048473 5230 levenberg_marquardt_strategy.cc:116] Linear solver failure. Failed to compute a step: CHOLMOD warning: Matrix not positive definite.
27 1.233725e+04 0.00e+00 1.18e+02 0.00e+00 0.00e+00 1.06e+15 1 4.46e-02 3.99e+00
28 1.233718e+04 6.92e-02 5.68e+01 3.52e-01 1.70e+00 3.18e+15 1 1.23e-01 4.12e+00
W0615 16:19:52.217936 5230 levenberg_marquardt_strategy.cc:116] Linear solver failure. Failed to compute a step: CHOLMOD warning: Matrix not positive definite.
29 1.233718e+04 0.00e+00 5.68e+01 0.00e+00 0.00e+00 1.59e+15 1 4.63e-02 4.16e+00
W0615 16:19:52.263574 5230 levenberg_marquardt_strategy.cc:116] Linear solver failure. Failed to compute a step: CHOLMOD warning: Matrix not positive definite.
30 1.233718e+04 0.00e+00 5.68e+01 0.00e+00 0.00e+00 3.97e+14 1 4.56e-02 4.21e+00
31 1.233714e+04 3.65e-02 5.88e+01 9.90e-02 1.93e+00 1.19e+15 1 1.21e-01 4.33e+00
32 1.233711e+04 3.32e-02 5.99e+01 2.59e-01 2.00e+00 3.57e+15 1 1.20e-01 4.45e+00
W0615 16:19:52.551789 5230 levenberg_marquardt_strategy.cc:116] Linear solver failure. Failed to compute a step: CHOLMOD warning: Matrix not positive definite.
33 1.233711e+04 0.00e+00 5.99e+01 0.00e+00 0.00e+00 1.79e+15 1 4.67e-02 4.50e+00
34 1.233708e+04 3.14e-02 6.16e+01 1.08e+00 2.00e+00 5.36e+15 1 1.20e-01 4.62e+00
W0615 16:19:52.721449 5230 levenberg_marquardt_strategy.cc:116] Linear solver failure. Failed to compute a step: CHOLMOD warning: Matrix not positive definite.
35 1.233708e+04 0.00e+00 6.16e+01 0.00e+00 0.00e+00 2.68e+15 1 4.93e-02 4.67e+00
W0615 16:19:52.765900 5230 levenberg_marquardt_strategy.cc:116] Linear solver failure. Failed to compute a step: CHOLMOD warning: Matrix not positive definite.
36 1.233708e+04 0.00e+00 6.16e+01 0.00e+00 0.00e+00 6.70e+14 1 4.44e-02 4.71e+00
37 1.233705e+04 2.50e-02 2.04e+01 9.75e-02 1.68e+00 2.01e+15 1 1.31e-01 4.84e+00
38 1.233704e+04 1.58e-02 1.87e+01 7.15e-01 1.95e+00 6.03e+15 1 1.22e-01 4.96e+00
W0615 16:19:53.064455 5230 levenberg_marquardt_strategy.cc:116] Linear solver failure. Failed to compute a step: CHOLMOD warning: Matrix not positive definite.
39 1.233704e+04 0.00e+00 1.87e+01 0.00e+00 0.00e+00 3.02e+15 1 4.59e-02 5.01e+00
W0615 16:19:53.108860 5230 levenberg_marquardt_strategy.cc:116] Linear solver failure. Failed to compute a step: CHOLMOD warning: Matrix not positive definite.
40 1.233704e+04 0.00e+00 1.87e+01 0.00e+00 0.00e+00 7.54e+14 1 4.44e-02 5.05e+00
41 1.233702e+04 1.51e-02 2.06e+01 1.12e-01 2.00e+00 2.26e+15 1 1.19e-01 5.17e+00
42 1.233701e+04 1.48e-02 2.10e+01 8.72e-01 1.99e+00 6.79e+15 1 1.24e-01 5.30e+00
W0615 16:19:53.398123 5230 levenberg_marquardt_strategy.cc:116] Linear solver failure. Failed to compute a step: CHOLMOD warning: Matrix not positive definite.
43 1.233701e+04 0.00e+00 2.10e+01 0.00e+00 0.00e+00 3.39e+15 1 4.64e-02 5.34e+00
44 1.233700e+04 1.42e-02 1.57e+01 1.28e+00 1.99e+00 1.00e+16 1 1.20e-01 5.46e+00
W0615 16:19:53.564965 5230 levenberg_marquardt_strategy.cc:116] Linear solver failure. Failed to compute a step: CHOLMOD warning: Matrix not positive definite.
45 1.233700e+04 0.00e+00 1.57e+01 0.00e+00 0.00e+00 5.00e+15 1 4.65e-02 5.51e+00
W0615 16:19:53.609803 5230 levenberg_marquardt_strategy.cc:116] Linear solver failure. Failed to compute a step: CHOLMOD warning: Matrix not positive definite.
46 1.233700e+04 0.00e+00 1.57e+01 0.00e+00 0.00e+00 1.25e+15 1 4.47e-02 5.55e+00
47 1.233698e+04 1.39e-02 2.11e+01 1.94e-01 2.00e+00 3.75e+15 1 1.22e-01 5.68e+00
W0615 16:19:53.777860 5230 levenberg_marquardt_strategy.cc:116] Linear solver failure. Failed to compute a step: CHOLMOD warning: Matrix not positive definite.
48 1.233698e+04 0.00e+00 2.11e+01 0.00e+00 0.00e+00 1.88e+15 1 4.61e-02 5.72e+00
49 1.233697e+04 1.36e-02 2.01e+01 7.07e-01 2.00e+00 5.62e+15 1 1.20e-01 5.84e+00
W0615 16:19:53.943998 5230 levenberg_marquardt_strategy.cc:116] Linear solver failure. Failed to compute a step: CHOLMOD warning: Matrix not positive definite.
50 1.233697e+04 0.00e+00 2.01e+01 0.00e+00 0.00e+00 2.81e+15 1 4.62e-02 5.89e+00
Solver Summary (v 2.0.0-eigen-(3.3.7)-lapack-suitesparse-(5.7.1)-cxsparse-(3.2.0)-eigensparse-no_openmp)
Original Reduced
Parameter blocks 22122 22122
Parameters 66462 66462
Residual blocks 83718 83718
Residuals 167436 167436
Minimizer TRUST_REGION
Sparse linear algebra library SUITE_SPARSE
Trust region strategy LEVENBERG_MARQUARDT
Given Used
Linear solver SPARSE_SCHUR SPARSE_SCHUR
Threads 1 1
Linear solver ordering AUTOMATIC 22106,16
Schur structure 2,3,9 2,3,9
Cost:
Initial 1.842900e+07
Final 1.233697e+04
Change 1.841667e+07
Minimizer iterations 51
Successful steps 37
Unsuccessful steps 14
Time (in seconds):
Preprocessor 0.419711
Residual only evaluation 0.517138 (36)
Jacobian & residual evaluation 1.818814 (37)
Linear solver 2.616899 (50)
Minimizer 5.472081
Postprocessor 0.007762
Total 5.899554
Termination: NO_CONVERGENCE (Maximum number of iterations reached. Number of iterations: 50.)
反復回数が増加するにつれて、全体的な誤差は減少し続けるはずです。
実行すると、最適化前の点群出力がinitial.ply、最適化後の点群出力がfinal.plyという2つのファイルが出力されます。
2 つの点群を表示するコマンドは次のとおりです。
meshlab initial.ply
meshlab final.ply
生成される画像は以下の通りです。
初期画像：
画像右下の出力情報も端末に出力されます。
Current Plugins Dir is: /usr/lib/x86_64-linux-gnu/meshlab/plugins
Shader directory found '/usr/share/meshlab/shaders', and it contains 19 gdp files
LOG: 0 Opened mesh initial.ply in 453 msec
LOG: 0 All files opened in 454 msec
最適化後:
画像の右下隅の出力情報も端末に出力されます。
Current Plugins Dir is: /usr/lib/x86_64-linux-gnu/meshlab/plugins
Shader directory found '/usr/share/meshlab/shaders', and it contains 19 gdp files
LOG: 0 Opened mesh final.ply in 435 msec
LOG: 0 All files opened in 436 msec
2.2 g2o で BA を解決
コード：
#include <g2o/core/base_vertex.h>
#include <g2o/core/base_binary_edge.h>
#include <g2o/core/block_solver.h>
#include <g2o/core/optimization_algorithm_levenberg.h>
#include <g2o/solvers/csparse/linear_solver_csparse.h>
#include <g2o/core/robust_kernel_impl.h>
#include <iostream>
#include "common.h"
#include "sophus/se3.hpp"
using namespace Sophus;
using namespace Eigen;
using namespace std;
/// 姿态和内参的结构
struct PoseAndIntrinsics {
PoseAndIntrinsics() {
}
/// set from given data address
explicit PoseAndIntrinsics(double *data_addr) {
rotation = SO3d::exp(Vector3d(data_addr[0], data_addr[1], data_addr[2]));
translation = Vector3d(data_addr[3], data_addr[4], data_addr[5]);
focal = data_addr[6];
k1 = data_addr[7];
k2 = data_addr[8];
}
/// 将估计值放入内存
void set_to(double *data_addr) {
auto r = rotation.log();
for (int i = 0; i < 3; ++i) data_addr[i] = r[i];
for (int i = 0; i < 3; ++i) data_addr[i + 3] = translation[i];
data_addr[6] = focal;
data_addr[7] = k1;
data_addr[8] = k2;
}
SO3d rotation;
Vector3d translation = Vector3d::Zero();
double focal = 0;
double k1 = 0, k2 = 0;
};
/// 位姿加相机内参的顶点，9维，前三维为so3，接下去为t, f, k1, k2
class VertexPoseAndIntrinsics : public g2o::BaseVertex<9, PoseAndIntrinsics> {
public:
EIGEN_MAKE_ALIGNED_OPERATOR_NEW;
VertexPoseAndIntrinsics() {
}
virtual void setToOriginImpl() override {
_estimate = PoseAndIntrinsics();
}
virtual void oplusImpl(const double *update) override {
_estimate.rotation = SO3d::exp(Vector3d(update[0], update[1], update[2])) * _estimate.rotation;
_estimate.translation += Vector3d(update[3], update[4], update[5]);
_estimate.focal += update[6];
_estimate.k1 += update[7];
_estimate.k2 += update[8];
}
/// 根据估计值投影一个点
Vector2d project(const Vector3d &point) {
Vector3d pc = _estimate.rotation * point + _estimate.translation;
pc = -pc / pc[2];
double r2 = pc.squaredNorm();
double distortion = 1.0 + r2 * (_estimate.k1 + _estimate.k2 * r2);
return Vector2d(_estimate.focal * distortion * pc[0],
_estimate.focal * distortion * pc[1]);
}
virtual bool read(istream &in) {
}
virtual bool write(ostream &out) const {
}
};
class VertexPoint : public g2o::BaseVertex<3, Vector3d> {
public:
EIGEN_MAKE_ALIGNED_OPERATOR_NEW;
VertexPoint() {
}
virtual void setToOriginImpl() override {
_estimate = Vector3d(0, 0, 0);
}
virtual void oplusImpl(const double *update) override {
_estimate += Vector3d(update[0], update[1], update[2]);
}
virtual bool read(istream &in) {
}
virtual bool write(ostream &out) const {
}
};
class EdgeProjection :
public g2o::BaseBinaryEdge<2, Vector2d, VertexPoseAndIntrinsics, VertexPoint> {
public:
EIGEN_MAKE_ALIGNED_OPERATOR_NEW;
virtual void computeError() override {
auto v0 = (VertexPoseAndIntrinsics *) _vertices[0];
auto v1 = (VertexPoint *) _vertices[1];
auto proj = v0->project(v1->estimate());
_error = proj - _measurement;
}
// use numeric derivatives
virtual bool read(istream &in) {
}
virtual bool write(ostream &out) const {
}
};
void SolveBA(BALProblem &bal_problem);
int main(int argc, char **argv) {
if (argc != 2) {
cout << "usage: bundle_adjustment_g2o bal_data.txt" << endl;
return 1;
}
BALProblem bal_problem(argv[1]);
bal_problem.Normalize();
bal_problem.Perturb(0.1, 0.5, 0.5);
bal_problem.WriteToPLYFile("initial.ply");
SolveBA(bal_problem);
bal_problem.WriteToPLYFile("final.ply");
return 0;
}
void SolveBA(BALProblem &bal_problem) {
const int point_block_size = bal_problem.point_block_size();
const int camera_block_size = bal_problem.camera_block_size();
double *points = bal_problem.mutable_points();
double *cameras = bal_problem.mutable_cameras();
// pose dimension 9, landmark is 3
typedef g2o::BlockSolver<g2o::BlockSolverTraits<9, 3>> BlockSolverType;
typedef g2o::LinearSolverCSparse<BlockSolverType::PoseMatrixType> LinearSolverType;
// use LM
auto solver = new g2o::OptimizationAlgorithmLevenberg(
g2o::make_unique<BlockSolverType>(g2o::make_unique<LinearSolverType>()));
g2o::SparseOptimizer optimizer;
optimizer.setAlgorithm(solver);
optimizer.setVerbose(true);
/// build g2o problem
const double *observations = bal_problem.observations();
// vertex
vector<VertexPoseAndIntrinsics *> vertex_pose_intrinsics;
vector<VertexPoint *> vertex_points;
for (int i = 0; i < bal_problem.num_cameras(); ++i) {
VertexPoseAndIntrinsics *v = new VertexPoseAndIntrinsics();
double *camera = cameras + camera_block_size * i;
v->setId(i);
v->setEstimate(PoseAndIntrinsics(camera));
optimizer.addVertex(v);
vertex_pose_intrinsics.push_back(v);
}
for (int i = 0; i < bal_problem.num_points(); ++i) {
VertexPoint *v = new VertexPoint();
double *point = points + point_block_size * i;
v->setId(i + bal_problem.num_cameras());
v->setEstimate(Vector3d(point[0], point[1], point[2]));
// g2o在BA中需要手动设置待Marg的顶点
v->setMarginalized(true);
optimizer.addVertex(v);
vertex_points.push_back(v);
}
// edge
for (int i = 0; i < bal_problem.num_observations(); ++i) {
EdgeProjection *edge = new EdgeProjection;
edge->setVertex(0, vertex_pose_intrinsics[bal_problem.camera_index()[i]]);
edge->setVertex(1, vertex_points[bal_problem.point_index()[i]]);
edge->setMeasurement(Vector2d(observations[2 * i + 0], observations[2 * i + 1]));
edge->setInformation(Matrix2d::Identity());
edge->setRobustKernel(new g2o::RobustKernelHuber());
optimizer.addEdge(edge);
}
optimizer.initializeOptimization();
optimizer.optimize(40);
// set to bal problem
for (int i = 0; i < bal_problem.num_cameras(); ++i) {
double *camera = cameras + camera_block_size * i;
auto vertex = vertex_pose_intrinsics[i];
auto estimate = vertex->estimate();
estimate.set_to(camera);
}
for (int i = 0; i < bal_problem.num_points(); ++i) {
double *point = points + point_block_size * i;
auto vertex = vertex_points[i];
for (int k = 0; k < 3; ++k) point[k] = vertex->estimate()[k];
}
}
ビルドでステートメントを実行します。
./bundle_adjustment_g2o /home/fighter/slam/slambook2/ch9/problem-16-22106-pre.txt
操作結果:
Header: 16 22106 83718iteration= 0 chi2= 8894422.962194 time= 0.253426 cumTime= 0.253426 edges= 83718 schur= 1 lambda= 227.832660 levenbergIter= 1
iteration= 1 chi2= 1772145.543625 time= 0.21523 cumTime= 0.468656 edges= 83718 schur= 1 lambda= 75.944220 levenbergIter= 1
iteration= 2 chi2= 752585.321418 time= 0.212928 cumTime= 0.681584 edges= 83718 schur= 1 lambda= 25.314740 levenbergIter= 1
iteration= 3 chi2= 402814.285609 time= 0.210998 cumTime= 0.892582 edges= 83718 schur= 1 lambda= 8.438247 levenbergIter= 1
iteration= 4 chi2= 284879.389455 time= 0.232436 cumTime= 1.12502 edges= 83718 schur= 1 lambda= 2.812749 levenbergIter= 1
iteration= 5 chi2= 238356.210033 time= 0.243281 cumTime= 1.3683 edges= 83718 schur= 1 lambda= 0.937583 levenbergIter= 1
iteration= 6 chi2= 193550.729802 time= 0.228287 cumTime= 1.59659 edges= 83718 schur= 1 lambda= 0.312528 levenbergIter= 1
iteration= 7 chi2= 146861.192839 time= 0.212535 cumTime= 1.80912 edges= 83718 schur= 1 lambda= 0.104176 levenbergIter= 1
iteration= 8 chi2= 122873.392728 time= 0.214303 cumTime= 2.02342 edges= 83718 schur= 1 lambda= 0.069451 levenbergIter= 1
iteration= 9 chi2= 97812.478436 time= 0.213007 cumTime= 2.23643 edges= 83718 schur= 1 lambda= 0.046300 levenbergIter= 1
iteration= 10 chi2= 80336.316621 time= 0.210887 cumTime= 2.44732 edges= 83718 schur= 1 lambda= 0.030867 levenbergIter= 1
iteration= 11 chi2= 65654.850651 time= 0.210773 cumTime= 2.65809 edges= 83718 schur= 1 lambda= 0.020578 levenbergIter= 1
iteration= 12 chi2= 55967.141021 time= 0.209642 cumTime= 2.86773 edges= 83718 schur= 1 lambda= 0.013719 levenbergIter= 1
iteration= 13 chi2= 53270.115686 time= 0.210373 cumTime= 3.07811 edges= 83718 schur= 1 lambda= 0.009146 levenbergIter= 1
iteration= 14 chi2= 35981.369897 time= 0.266059 cumTime= 3.34416 edges= 83718 schur= 1 lambda= 0.006097 levenbergIter= 2
iteration= 15 chi2= 32092.173309 time= 0.316057 cumTime= 3.66022 edges= 83718 schur= 1 lambda= 0.016259 levenbergIter= 3
iteration= 16 chi2= 31154.877381 time= 0.261828 cumTime= 3.92205 edges= 83718 schur= 1 lambda= 0.021679 levenbergIter= 2
iteration= 17 chi2= 30773.690800 time= 0.211655 cumTime= 4.1337 edges= 83718 schur= 1 lambda= 0.014453 levenbergIter= 1
iteration= 18 chi2= 29079.971263 time= 0.266129 cumTime= 4.39983 edges= 83718 schur= 1 lambda= 0.012508 levenbergIter= 2
iteration= 19 chi2= 28481.944292 time= 0.26298 cumTime= 4.66281 edges= 83718 schur= 1 lambda= 0.016678 levenbergIter= 2
iteration= 20 chi2= 28439.938323 time= 0.210573 cumTime= 4.87339 edges= 83718 schur= 1 lambda= 0.011118 levenbergIter= 1
iteration= 21 chi2= 27171.835892 time= 0.264091 cumTime= 5.13748 edges= 83718 schur= 1 lambda= 0.011153 levenbergIter= 2
iteration= 22 chi2= 26749.623597 time= 0.265487 cumTime= 5.40296 edges= 83718 schur= 1 lambda= 0.014871 levenbergIter= 2
iteration= 23 chi2= 26674.555645 time= 0.209385 cumTime= 5.61235 edges= 83718 schur= 1 lambda= 0.009914 levenbergIter= 1
iteration= 24 chi2= 26089.998120 time= 0.262896 cumTime= 5.87524 edges= 83718 schur= 1 lambda= 0.010288 levenbergIter= 2
iteration= 25 chi2= 25877.861699 time= 0.264081 cumTime= 6.13933 edges= 83718 schur= 1 lambda= 0.013717 levenbergIter= 2
iteration= 26 chi2= 25834.638622 time= 0.213956 cumTime= 6.35328 edges= 83718 schur= 1 lambda= 0.009145 levenbergIter= 1
iteration= 27 chi2= 25570.298632 time= 0.264777 cumTime= 6.61806 edges= 83718 schur= 1 lambda= 0.011127 levenbergIter= 2
iteration= 28 chi2= 25457.520755 time= 0.26327 cumTime= 6.88133 edges= 83718 schur= 1 lambda= 0.011716 levenbergIter= 2
iteration= 29 chi2= 25380.650160 time= 0.26591 cumTime= 7.14724 edges= 83718 schur= 1 lambda= 0.012090 levenbergIter= 2
iteration= 30 chi2= 25362.215118 time= 0.211995 cumTime= 7.35923 edges= 83718 schur= 1 lambda= 0.008060 levenbergIter= 1
iteration= 31 chi2= 25202.452901 time= 0.263831 cumTime= 7.62306 edges= 83718 schur= 1 lambda= 0.008800 levenbergIter= 2
iteration= 32 chi2= 25122.596797 time= 0.263859 cumTime= 7.88692 edges= 83718 schur= 1 lambda= 0.009613 levenbergIter= 2
iteration= 33 chi2= 25115.107638 time= 0.214994 cumTime= 8.10192 edges= 83718 schur= 1 lambda= 0.006408 levenbergIter= 1
iteration= 34 chi2= 24967.189622 time= 0.269087 cumTime= 8.371 edges= 83718 schur= 1 lambda= 0.006268 levenbergIter= 2
iteration= 35 chi2= 24910.138884 time= 0.263436 cumTime= 8.63444 edges= 83718 schur= 1 lambda= 0.008358 levenbergIter= 2
iteration= 36 chi2= 24867.273980 time= 0.261406 cumTime= 8.89584 edges= 83718 schur= 1 lambda= 0.006277 levenbergIter= 2
iteration= 37 chi2= 24848.840518 time= 0.262723 cumTime= 9.15857 edges= 83718 schur= 1 lambda= 0.008370 levenbergIter= 2
iteration= 38 chi2= 24847.135479 time= 0.210439 cumTime= 9.36901 edges= 83718 schur= 1 lambda= 0.005580 levenbergIter= 1
iteration= 39 chi2= 24798.075555 time= 0.26268 cumTime= 9.63169 edges= 83718 schur= 1 lambda= 0.007249 levenbergIter= 2
同様に、最適化前後の 2 つの点群の画像を表示できます。表示結果は次のとおりです。
最適化前:
最適化後:
初期画像:
画像の右下の出力情報も出力されます。ターミナル
Current Plugins Dir is: /usr/lib/x86_64-linux-gnu/meshlab/plugins
Shader directory found '/usr/share/meshlab/shaders', and it contains 19 gdp files
LOG: 0 Opened mesh initial.ply in 534 msec
LOG: 0 All files opened in 535 msec
最適化後:
画像の右下隅の出力情報も端末に出力されます。
Current Plugins Dir is: /usr/lib/x86_64-linux-gnu/meshlab/plugins
Shader directory found '/usr/share/meshlab/shaders', and it contains 19 gdp files
LOG: 0 Opened mesh final.ply in 673 msec
LOG: 0 All files opened in 676 msec
3. 発生した問題と解決策
3.1 .ply ファイルを表示すると警告が表示される
- 初めてファイルを表示するコマンドを実行すると、ターミナルに警告が表示されます。
Current Plugins Dir is: /usr/lib/x86_64-linux-gnu/meshlab/plugins
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
Warning! a default param was not found in the saved settings. This should happen only on the first run...
..........
解決策:
対応するファイルの場所でコマンドを再度実行します。