Optimal 3D Modeling of Human Manikin Using Bone Structure and Cluster Analysis 


Vol. 62,  No. 6, pp. 337-345, Dec.  2025
10.12772/TSE.2025.62.337


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  Abstract

Large-sized objects such as human manikins need a proper a priori mesh segmentation process for successful 3D printing. This paper applied well-known statistical mesh clustering functions, including k-means, k-medoids, DBSCAN, and pairwise distance. Especially, an inventive clustering metric, designated as point-to-bone distance, was proposed to take advantage of bone structure which can be acquired easily from free software such as Adobe Mixamo. Furthermore, the cut parts were oriented to the optimal directions, in which the minimal support structure was expected, using our previous work. Now any textile or apparel scientists can easily 3D-print their human manikins with arbitrary shapes and sizes with the help of python language.

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  Cite this article

[IEEE Style]

설인환, "Optimal 3D Modeling of Human Manikin Using Bone Structure and Cluster Analysis," Textile Science and Engineering, vol. 62, no. 6, pp. 337-345, 2025. DOI: 10.12772/TSE.2025.62.337.

[ACM Style]

설인환. 2025. Optimal 3D Modeling of Human Manikin Using Bone Structure and Cluster Analysis. Textile Science and Engineering, 62, 6, (2025), 337-345. DOI: 10.12772/TSE.2025.62.337.

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pISSN : 1225 - 1089
eISSN : 2288 - 6419

한국연구재단 우수등재학술지 유지 (2022년)