Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: May 30, 2026

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

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

Published on: August 13, 2014

Mesh segmentation with concavity-aware fields.

Oscar Kin-Chung Au¹, Youyi Zheng, Menglin Chen

¹School of Creative Media, The City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong. kincau@cityu.edu.hk

IEEE Transactions on Visualization and Computer Graphics

|July 27, 2011

Summary

This summary is machine-generated.

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

Effect of physical exercise on the subjective wellbeing of middle-aged and older adults: chain mediating role of self-esteem and psychological resilience.

Frontiers in public health·2026

Same author

Predicting anemia treatment outcomes in maintenance hemodialysis patients using multiple machine learning models.

BMC medical informatics and decision making·2026

Same author

Development and Application of Organoids for Toxicology Studies.

Journal of applied toxicology : JAT·2026

Same author

Research on Path Planning for Fire Evacuation Using the Enhanced Hiking Optimization Algorithm.

Biomimetics (Basel, Switzerland)·2026

Same author

Global research trends and knowledge gaps in chronic pharyngitis: A bibliometric analysis (2007-2025).

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery·2026

Same author

Effect of Exercise on Parathyroid Hormone Levels in Dialysis Patients: A Systematic Review and Meta-Analysis.

Hemodialysis international. International Symposium on Home Hemodialysis·2026

Same journal

MesoSplats: Texture Synthesis with Gaussian Splatting.

IEEE transactions on visualization and computer graphics·2026

Same journal

GLLA: A Unified Force-Directed Graph Layout Framework Supporting Local Adjustments.

IEEE transactions on visualization and computer graphics·2026

Same journal

Multi-Perception Crowd: Learning to combine entity and implicit perception for diverse crowd simulation.

IEEE transactions on visualization and computer graphics·2026

Same journal

Hiding in Plain Sight: Camouflaging Real-world Objects.

IEEE transactions on visualization and computer graphics·2026

Same journal

RTF2Mesh: Restricted Tangent Face Based Mesh Compression With Neural Displacement Fields.

IEEE transactions on visualization and computer graphics·2026

Same journal

Practical Occluder Generation for Mobile Games.

IEEE transactions on visualization and computer graphics·2026

See all related articles

This study introduces an efficient automatic mesh segmentation algorithm using shape concavity. The method identifies seams and cuts effectively, achieving results comparable to complex state-of-the-art approaches.

Area of Science:

Computer Graphics
Computational Geometry
Geometric Modeling

Background:

Automatic mesh segmentation is crucial for various applications.
Existing methods often rely on complex features or user interaction.
There is a need for simple, efficient, and accurate segmentation techniques.

Purpose of the Study:

To develop a novel automatic mesh segmentation algorithm.
To leverage shape concavity information for seam detection.
To achieve high-quality segmentation comparable to state-of-the-art methods.

Main Methods:

Utilized concavity-sensitive scalar fields derived from a Laplacian system.
Employed a novel concavity-sensitive weighting scheme for field computation.
Applied a score-based greedy algorithm on isolines for cut selection.

More Related Videos

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Related Experiment Videos

Last Updated: May 30, 2026

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

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

Published on: August 13, 2014

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

Main Results:

Successfully identified concave creases and seams using concavity-aware fields.
Demonstrated efficient evaluation of candidate cuts.
Achieved segmentation quality superior to or comparable with existing methods.

Conclusions:

The proposed algorithm offers a simple and efficient approach to mesh segmentation.
Shape concavity is a powerful feature for automatic seam detection.
The method provides a competitive alternative to more complex segmentation techniques.