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Related Concept Videos

Centroid of a Body01:16

Centroid of a Body

The centroid is an important concept in engineering, physics, and mechanics. It is the geometric center of a body. It always lies within the body except in cases with holes or cavities. When the material that a body is composed of is uniform or homogeneous, the centroid coincides with its center of mass or the center of gravity.
For a homogeneous body with constant density, the centroid can usually be found using equations representing a balance of the moments of the body's volume. If the...
Centroid of a Body: Problem Solving01:03

Centroid of a Body: Problem Solving

The centroid of a body is a crucial concept in engineering and physics. Finding the centroid of a body can help determine its stability, its balance point, and even its design. In this context, consider a thin wire bent in the form of a quarter circular arc. Polar coordinates are used to calculate the centroid. The wire is first divided into small differential elements of a length equal to the radius multiplied by the differential angle.
The x-coordinates and y-coordinates of each element's...

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Related Experiment Video

Updated: Jun 4, 2026

Segmentation and Linear Measurement for Body Composition Analysis using Slice-O-Matic and Horos
13:35

Segmentation and Linear Measurement for Body Composition Analysis using Slice-O-Matic and Horos

Published on: March 21, 2021

Isomap transform for segmenting human body shapes.

P Cerveri1, K J Sarro, M Marchente

  • 1Bioengineering Department , Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano, Italy. pietro.cerveri@polimi.it

Computer Methods in Biomechanics and Biomedical Engineering
|March 2, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel 3D human body segmentation method using Isomap transform and Hoshen-Kopelman clustering. It accurately separates body parts for markerless motion analysis.

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Area of Science:

  • Computer Vision
  • Medical Imaging
  • Biomechanics

Background:

  • 3D human body segmentation from volume data is complex.
  • Direct Euclidean clustering is often unsolvable.
  • Markerless motion analysis requires accurate segmentation.

Purpose of the Study:

  • To develop an original method for 3D human body segmentation.
  • To improve accuracy in joint center and rotation axis localization.
  • To enable markerless motion analysis.

Main Methods:

  • Isomap (isometric feature mapping) transform of volume data.
  • Mapping 3D articulated posture to Da Vinci's Vitruvian man pose.
  • Hoshen-Kopelman clustering on spherical shells for point grouping.
  • Shepard interpolation for back-mapping to original volume space.

Main Results:

  • Successful unrolling, separation, and topology recovery of human body parts.
  • Automatic grouping of points into labelled principal curves.
  • Reliability of <2 cm for joint centers and <3° for rotation axes.
  • Demonstrated validity across diverse postures.

Conclusions:

  • The proposed method offers a robust solution for 3D human body segmentation.
  • Achieved high accuracy in joint localization, suitable for markerless motion analysis.
  • Presents a potential tool for advanced biomechanical studies.