A novel algorithm for 3D-printing technology was proposed to generate large-scale objects, especially A-shaped manikins or 3D human body scan data. Most of the conventional 3D printers have a finite printing volume, and it is the users’ work to convert the target object into a printable size. In this study, an automatic three-step segmentation strategy was applied to the raw manikin mesh data until the final pieces had a smaller size than the 3D printer’s maximum printing volume, which is generally called “beam length”. Human body feature point information was adopted for fashion and textile researchers to easily specify the desired cutting positions. A simple bounding box, especially orienting bounding box, and modified Boolean operator were proposed to extract the specified segments with computational stability. The proposed method was applied to graphically synthesized manikin data, and 1/8, 1/4, and 1/2 scale manikins were successfully printed, minimizing the amount of support structure.

中文翻译：

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使用边界框和人体特征点对A形人体模型进行自动分割和3D打印

提出了一种新颖的3D打印技术算法，用于生成大规模物体，尤其是A形人体模型或3D人体扫描数据。大多数传统3D打印机的打印量是有限的，将目标对象转换为可打印尺寸是用户的工作。在这项研究中，将自动三步分割策略应用于原始人体模型网格数据，直到最终碎片的尺寸小于3D打印机的最大打印量（通常称为“光束长度”）为止。时装和纺织品研究人员采用了人体特征点信息，以轻松指定所需的切割位置。提出了一种简单的边界框，尤其是定向边界框，以及改进的布尔算子来提取具有计算稳定性的指定段。