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The Hakka cardigan stands as a quintessential representation of traditional Hakka attire, embodying not only the rich cultural heritage of a nation but also serving as a global cultural treasure. In this academic paper, we focus on a representative model to showcase the development of an autonomous 3D scanning system founded on an offline point cloud generation algorithm. Through a meticulous process involving the emulation of clothing pattern restoration, we employ a diverse array of software tools including Photoshop, Autodesk Maya, and CORELDRAW, harnessing graphic and image processing techniques to seamlessly transition from two-dimensional pattern restoration to a three-dimensional realm. This study revolves around the establishment of an autonomous 3D scanning system centered on a representative model, leveraging an offline point cloud generation algorithm. We incorporate the La-place mesh deformation algorithm to execute conformal transformations on neighboring vertices of motion vertices, while delving into the fundamental methodologies behind digital restoration and the three-dimensional virtual presentation of Hakka cardigans. Our experiments culminate in the measurement of six three-dimensional clothing pieces, revealing absolute deviation between the model and the actual clothing. Furthermore, when we compare the automatic measurements from 200 3D scanned human bodies with their manually obtained counterparts, the displayed measurement error hovers at approximately 0.5 cm. This research endeavor charts an expedited pathway to achieve digital restoration and three-dimensional virtual representation of Hakka cardigans. It not only offers a novel perspective for the digital revitalization of traditional clothing but also serves as a valuable augmentation to contemporary methods of preserving traditional clothing.
Qianqian Yu (2023) studied this question.