Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

109
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
109

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Cyclists' perceived safety on intersections and roundabouts - A qualitative bicycle simulator study.

Journal of safety research·2023
Same author

Configurable Sensor Model Architecture for the Development of Automated Driving Systems.

Sensors (Basel, Switzerland)·2021
See all related articles

Related Experiment Video

Updated: Sep 30, 2025

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

24.7K

Methodology for a reverse engineering process chain with focus on customized segmentation and iterative closest point

Stephan Mönchinger1, Robert Schröder1, Rainer Stark2

  • 1Fraunhofer IPK, Germany.

Methodsx
|March 11, 2022
PubMed
Summary

This study introduces an automated method for detecting deviations between digital models and actual construction states in one-off projects. The software uses point cloud segmentation and a customized iterative closest point algorithm for accurate 3D scan data assessment.

Keywords:
Cad repositioningICPOpen source developmentPCLReverse engineeringSegmentation

More Related Videos

Evaporation-reducing Culture Condition Increases the Reproducibility of Multicellular Spheroid Formation in Microtiter Plates
11:24

Evaporation-reducing Culture Condition Increases the Reproducibility of Multicellular Spheroid Formation in Microtiter Plates

Published on: March 7, 2017

7.1K
A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
12:49

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

13.0K

Related Experiment Videos

Last Updated: Sep 30, 2025

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
12:08

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

24.7K
Evaporation-reducing Culture Condition Increases the Reproducibility of Multicellular Spheroid Formation in Microtiter Plates
11:24

Evaporation-reducing Culture Condition Increases the Reproducibility of Multicellular Spheroid Formation in Microtiter Plates

Published on: March 7, 2017

7.1K
A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
12:49

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

13.0K

Area of Science:

  • Construction Engineering
  • Computer-Aided Design
  • Reverse Engineering

Background:

  • One-off construction relies heavily on manual processes and digital models.
  • Discrepancies between as-built conditions and digital models necessitate manual updates.
  • Automated assessment of 3D scan data in one-off construction is underdeveloped, especially for SMEs.

Purpose of the Study:

  • To develop an automated method for detecting and correcting deviations in one-off construction projects.
  • To enable consistent use of digital models by aligning them with the actual construction state.
  • To accelerate progress in the application of digital models within the construction industry.

Main Methods:

  • Implementing a method based on "Segmentation of Unorganized Points and Recognition of Simple Algebraic Surfaces".
  • Customizing the iterative closest point (ICP) algorithm for deviation analysis.
  • Developing a software prototype within an open-source environment, integrated into a reverse engineering framework.

Main Results:

  • The software prototype effectively segments unorganized points and recognizes simple algebraic surfaces.
  • A customized ICP algorithm (CICP) enables accurate deviation analysis and model repositioning.
  • The developed system provides a framework for automated assessment of 3D scan data.

Conclusions:

  • The proposed automated method significantly improves the alignment of digital models with as-built construction data.
  • The open-source software accelerates the consistent use of digital models in one-off construction.
  • This approach has the potential to advance automated 3D scan data assessment for small and medium enterprises in construction.