Dr. KID is an algorithm that uses isometric decomposition for the physicalization of potato-shaped organic models in a puzzle fashion. The algorithm begins with creating a simple, regular triangular surface mesh of organic shapes, followed by iterative k-means clustering and remeshing. For clustering, we need similarity between triangles (segments) which is defined as a distance function. The distance function maps each triangle's shape to a single point in the virtual 3D space. Thus, the distance between the triangles indicates their degree of dissimilarity. K-means clustering uses this distance and sorts of segments into k classes. After this, remeshing is applied to minimize the distance between triangles within the same cluster by making their shapes identical. Clustering and remeshing are repeated until the distance between triangles in the same cluster reaches an acceptable threshold. We adopt a curvature-aware strategy to determine the surface thickness and finalize puzzle pieces for 3D printing. Identical hinges and holes are created for assembling the puzzle components. For smoother outcomes, we use triangle subdivision along with curvature-aware clustering, generating curved triangular patches for 3D printing. Our algorithm was evaluated using various models, and the 3D-printed results were analyzed. Findings indicate that our algorithm performs reliably on target organic shapes with minimal loss of input geometry.

翻译：Dr. KID是一种采用等距分解实现马铃薯状有机模型拼图式实体化的算法。该算法首先构建有机形态的简单规则三角曲面网格，随后迭代执行k均值聚类与重网格化。在聚类过程中，需定义三角形（曲面片）间的相似度度量，该度量通过距离函数实现——将每个三角形形状映射至虚拟三维空间中的单一点，从而以点间距离表征形状差异。k均值聚类算法利用该距离将曲面片划分为k个类别。随后通过重网格化，使同类曲面片形状趋于一致，以最小化簇内三角形距离。重复执行聚类与重网格化流程，直至同类三角形间距降至可接受阈值。最终采用曲率感知策略确定曲面厚度，完成3D打印拼图组件的生成，并设计匹配的铰链与孔洞实现拼装。为获得更平滑效果，算法结合曲率感知聚类对三角形进行细分，生成适用于3D打印的弧形三角面片。经多模型测试与3D打印结果分析表明，本算法在保持输入几何特征最小损耗的前提下，对目标有机形态具有可靠处理能力。