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

You might also read

Related Articles

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

Sort by
Same author

Efficacy of ProC6C-AlOH/Matrix-M against Plasmodium falciparum infection and mosquito transmission: a phase 2, randomised, controlled human malaria infection study.

The Lancet. Infectious diseases·2025
Same author

Predictive Modeling for Personalized Three-Dimensional Burn Injury Assessments.

Journal of burn care & research : official publication of the American Burn Association·2019
Same author

The Importance of a Three-dimensional-Based Approach With Personalized Models for Accurately Assessing TBSA.

Journal of burn care & research : official publication of the American Burn Association·2017
Same author

Geometric modeling of pelvic organs.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2012
Same journal

Making Learning Visible: Turning Public Engagement into Evidence for Academic Learning.

IEEE computer graphics and applications·2026
Same journal

LlymX: Multimodal LLM-Augmented XR for Context-Aware Information Access.

IEEE computer graphics and applications·2026
Same journal

Dynamic Gaussian-Based Digital Twin Reconstruction of Articulated Multi-Joint Objects.

IEEE computer graphics and applications·2026
Same journal

Steiner and Poisson Traversal Initializations: Initial Curve Optimization for Geometric Flow-based Surface Filling.

IEEE computer graphics and applications·2026
Same journal

Insight Into the Insight Toolkit.

IEEE computer graphics and applications·2026
Same journal

Ambient Analytics: Calm Technology for Immersive Visualization and Sensemaking.

IEEE computer graphics and applications·2026
See all related articles

Related Experiment Video

Updated: Jul 1, 2026

Fabrication and Implementation of a Reference-Free Traction Force Microscopy Platform
08:10

Fabrication and Implementation of a Reference-Free Traction Force Microscopy Platform

Published on: October 6, 2019

Graph Pattern Matching based reassembly - 3DGPM.

Ibrahim Diarra, Florian Beguet, Sandrine Lanquetin

    IEEE Computer Graphics and Applications
    |June 29, 2026
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a novel graph-based method for 3D object reconstruction, enhancing artifact reassembly by analyzing surface patch arrangements. The approach improves accuracy and robustness for fragmented archaeological finds.

    More Related Videos

    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

    Origami Inspired Self-assembly of Patterned and Reconfigurable Particles
    12:33

    Origami Inspired Self-assembly of Patterned and Reconfigurable Particles

    Published on: February 4, 2013

    Related Experiment Videos

    Last Updated: Jul 1, 2026

    Fabrication and Implementation of a Reference-Free Traction Force Microscopy Platform
    08:10

    Fabrication and Implementation of a Reference-Free Traction Force Microscopy Platform

    Published on: October 6, 2019

    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

    Origami Inspired Self-assembly of Patterned and Reconfigurable Particles
    12:33

    Origami Inspired Self-assembly of Patterned and Reconfigurable Particles

    Published on: February 4, 2013

    Area of Science:

    • Computer Vision
    • Computational Geometry
    • Archaeological Science

    Background:

    • Reassembling fragmented 3D objects, especially archaeological artifacts, presents significant challenges due to surface degradation and material variations.
    • Existing methods often struggle with noise and incomplete data, limiting reconstruction accuracy.

    Purpose of the Study:

    • To develop a robust graph-based method for matching and reassembling fragmented 3D objects.
    • To improve the accuracy and resilience of 3D reconstruction for degraded archaeological artifacts.

    Main Methods:

    • A novel graph-based approach integrating geometric and topological features to analyze surface patch arrangements.
    • Utilizing Reeb graph partitioning for fragment segmentation and constructing an adjacency graph to encode spatial relationships.
    • Employing the shape index for local geometry description and pairwise matching via structural pattern comparison, filtered by geometric consistency.

    Main Results:

    • Achieved 80% and 95% pairwise matching recall on two public datasets.
    • Successfully reconstructed objects comprising up to 62 fragments.
    • Demonstrated superior performance compared to classical and recent AI-based reconstruction methods.

    Conclusions:

    • The proposed graph-based method offers a robust and accurate solution for reassembling fragmented 3D objects, particularly archaeological artifacts.
    • The technique's focus on surface patch arrangements enhances resilience to erosion and noise, outperforming existing approaches.