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是一种算法,它使用等距分解以拼图的方式物理化土豆形有机模型。该算法以创建一个简单的规则三角形表面网格开始,然后进行迭代的k-means聚类和重构。为了进行聚类,我们需要一个相似性距离函数,该函数将每个三角形的形状映射到虚拟三维空间中的单个点。因此,三角形之间的距离表示它们的差异程度。K-means聚类使用这个距离将段划分为k类。之后,进行重构以最小化同一类别内三角形之间的距离,使它们的形状相同。重复聚类和重构直到同一类别内的三角形之间的距离达到可接受的阈值为止。我们采用曲率感知策略来确定表面厚度,并为组装拼图组件创建相同的铰链和孔。为了获得更平稳的结果,我们使用三角形细分以及曲率感知聚类生成曲线三角形片段进行三维打印。我们的算法使用各种模型进行了评估,并分析了三维打印结果。研究结果表明,我们的算法在目标有机形状上表现可靠,且最小化输入几何形状的丢失。