Resampling of 3D Triangular Foot Models Based on Cloth Simulation

To improve the comparability and operability of three-dimensional (3D) triangular foot models, this study proposes a resampling method for 3D triangular foot models based on cloth simulation. This method refers to a 3D triangular foot template and 3D foot models to be resampled. The foot template is regarded as a fabric with elasticity and deformability, and the foot model to be resampled is regarded as a rigid body. First, the rigid body model is scaled down to be completely enclosed by the foot template. Then, the rigid body model gradually enlarges and returns to its original size. During the enlargement process, the rigid body model will push against the foot template. Finally, the shapes of the foot template and the rigid body model become exactly the same. The final deformed foot templates were saved as the resampled triangular foot models, which could be used as the original foot models to be resampled. In this study, the effects of different 3D triangular foot templates and various cloth simulation parameters on the resampling results were investigated. A statistical analysis of the errors of the resampled triangular foot models was conducted. The results demonstrate that the same foot template can represent 3D triangular foot models of different shapes with this resampling method. That is to say, foot models processed with the same template exhibit the same number of vertices and consistent triangular topological structure. When resampling 216 sets of 3D triangular foot models using the template with 2184 vertices, the average Hausdorff distance was calculated as 0.0466. For the template with 8085 vertices, the average Hausdorff distance of the 216 model sets was 0.0464. For the template with 19,752 vertices, the average Hausdorff distance of the 216 model sets reached 0.0494. This method can provide technical support for the automated measurement and analysis of 3D triangular foot models.

• Publication year

  2026

• Venue

  Applied Sciences

• Publication date

  2026-02-27

• Fields of study

  Not labeled

• Identifiers
  DOI 10.3390/app16052298
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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