3d industrial r econstruction by fitting csg models to a combination of images and point clouds l.jpg
This presentation is the property of its rightful owner.
Sponsored Links
1 / 24

3D industrial r econstruction by fitting CSG models to a combination of images and point clouds PowerPoint PPT Presentation


  • 79 Views
  • Uploaded on
  • Presentation posted in: General

3D industrial r econstruction by fitting CSG models to a combination of images and point clouds. Tahir Rabbani Frank van den Heuvel. Overview. Introduction The approach to modelling Model fitting: point clouds and images Fitting experiments: cylinder and box Conclusions. Introduction.

Download Presentation

3D industrial r econstruction by fitting CSG models to a combination of images and point clouds

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


3d industrial r econstruction by fitting csg models to a combination of images and point clouds l.jpg

3D industrialreconstruction by fitting CSG models to a combination of images and point clouds

Tahir Rabbani

Frank van den Heuvel


Overview l.jpg

Overview

  • Introduction

  • The approach to modelling

  • Model fitting: point clouds and images

  • Fitting experiments: cylinder and box

  • Conclusions


Introduction l.jpg

Introduction

  • New approach for semi-automatic reverse engineering of industrial sites from images presented to ISPRS congress Amsterdam 2000


Introduction4 l.jpg

Introduction

  • New approach for semi-automatic reverse engineering of industrial sites from images presented to ISPRS congress Amsterdam 2000

  • 2001: Automated 3D reconstruction of industrial installations from laser and image data

    • EU-project: Services and Training through Augmented Reality (STAR)

    • Partners: Siemens, KULeuven, EPFL, UNIGE, Realviz


Modelling p ipeline overview l.jpg

Modelling Pipeline Overview

1. Segmentation

Range data

Images

2. Object Recognition

CAD model

Database

User

Input

3. Constraint detection

4. Integrated adjustment


Modelling p ipeline 1 4 l.jpg

Modelling Pipeline(1/4)

  • Segmentation

    • Grouping points of surface patches


Modelling p ipeline 2 4 l.jpg

Modelling Pipeline(2/4)

  • Segmentation

    • Grouping points of surface patches

  • Object Recognition

    • Finding planes and cylinders


Modelling p ipeline 3 4 l.jpg

Modelling Pipeline(3/4)

  • Segmentation

    • Grouping points of surface patches

  • Object Recognition

    • Finding planes and cylinders

  • Constraint detection

    • Completing the CSG model


Constructive solid geometry csg l.jpg

Constructive Solid Geometry (CSG)

  • CSG-tree:

    • primitives (box, cylinder, …)

    • shape, pose parameters

    • Constraints on parameters


Modelling p ipeline 4 4 l.jpg

Modelling Pipeline(4/4)

  • Segmentation

    • Grouping points of surface patches

  • Object Recognition

    • Finding planes and cylinders

  • Constraint detection

    • Completing the CSG model

  • Integrated adjustment

    • Fitting of CSG model to range data and imagery


Integrated adjustment l.jpg

Integrated adjustment

  • Least-squares adjustment integrating:

    • Fitting of CSG model to point cloud

    • Fitting of projected model to images

    • Geometric constraints on (relative) pose and shape


Fitting to a point cloud l.jpg

Fitting to a point cloud

  • Minimise sum of squared distances in object space

= shortest distance of a given point

from

= model surface defined by

= 3D laser points


Fitting to images l.jpg

Fitting to images

  • Minimise sum of squared distances in image space

= shortest distance of a given point

from

= back projected CSG model with parameters

= 2D image points


Fitting solution l.jpg

Fitting – Solution

  • Levenberg-Marquardt method:

    • Improved convergence compared to least-squares

    • Identical to least-squares for λ=0

  • Least-squares adjustment:

    • Assessment of precision through error propagation

    • Analysis of quality of fit (residuals)


Experiments l.jpg

Experiments

  • Cylinder fitting:

    • 6179 laser points Cyrax2500 (σ=5mm)

    • 3 images, 383 points Calibrated Coolpix5000 (σ=1pixel)

  • Box fitting:

    • 25162 laser points

    • 3 images, 416 points


Experiment cylinder fitting results l.jpg

Experiment: cylinder fitting results

  • Standard deviations

Parameter LaserIntegrated

Length (mm) 1.86

Radius (mm) 0.630.57

X (mm) 0.840.76

Y (mm) 1.340.86

Z (mm)119.901.65

t02.3e-32.0e-3

t14.0e-32.9e-3

t23.6e-12.4e-1


Experiment cylinder fitting results17 l.jpg

Standard deviations:

Experiment: cylinder fitting results

  • Conclusions:

    • Only laser: length and position in Z undetermined

    • Integrated: better than 2mm, similar results for using only 1 or 2 images

Parameter LaserIntegrated

Length (mm) 1.86

Radius (mm) 0.630.57

X (mm) 0.840.76

Y (mm) 1.340.86

Z (mm)119.901.65

t02.3e-32.0e-3

t14.0e-32.9e-3

t23.6e-12.4e-1


Experiment cylinder fitting results18 l.jpg

Residuals (laser)

Experiment: cylinder fitting results


Experiment box fitting results l.jpg

Experiment: box fitting results

  • Standard deviations

Parameter LaserIntegrated

X size (mm) 2.890.66

Y size (mm) 0.53

Z size (mm) 0.32

X (mm) 3.080.65

Y (mm) 0.550.16

Z (mm)389.840.31

q04.0e-23.0e-2

q12.4e-41.0e-4

q25.2e-45.0e-5

q33.4e-42.0e-4


Experiment box fitting results20 l.jpg

Experiment: box fitting results

  • Standard deviations

  • Conclusions:

    • Only laser: sizes in Y and Z undetermined

    • Size in X highly correlated with position in X

    • Position in Z undetermined

    • Integrated: better than 1mm, similar results for using only 1 or 2 images

Parameter LaserIntegrated

X size (mm) 2.890.66

Y size (mm) 0.53

Z size (mm) 0.32

X (mm) 3.080.65

Y (mm) 0.550.16

Z (mm)389.840.31

q04.0e-23.0e-2

q12.4e-41.0e-4

q25.2e-45.0e-5

q33.4e-42.0e-4


Experiment box fitting results21 l.jpg

Experiment: box fitting results

  • Residuals (laser)


Why fusion of laser and image data l.jpg

Why fusion of laser and image data?

  • Instrumentation developments

    • Scanners with integrated high-resolution camera

  • Accuracy improvement

    • Complementary: Laser for surfaces, image for edges

  • Flexibility of image acquisition: Completeness

  • Non-geometric information (What is there?)


Future conclusions l.jpg

Future / Conclusions

  • Future research:

    • Estimation of exterior orientation parameters

    • Integration of geometric constraints

  • Conclusions:

    • Integrated adjustment of laser and image data developed and analysed


Future conclusions24 l.jpg

Future / Conclusions

  • Future research:

    • Estimation of exterior orientation parameters

    • Integration of geometric constraints

  • Conclusions:

    • Integrated adjustment of laser and image data developed and analysed

    • Laser and image data are complementary:

      Keep the best of both worlds !


  • Login