This paper presents CardBoardiZer, a rapid cardboard based prototyping platform that allows everyday sculptural 3D models to be easily customized, articulated and folded. Furthermore, augmenting articulated features to a desired model requires time-consuming synthesis of interconnected joints. We found origami designs are often characterized by pre-synthesized patterns and automated algorithms. Future work includes an iterative application of this algorithm to progressively sever features of the mesh left from previous sub-mesh removals.Ĭomputer-aided design of flat patterns allows designers to prototype foldable 3D objects made of heterogeneous sheets of material. The achieved segmentations properly locate most manufacturing features, although it requires human interaction to avoid over segmentation. We present tests of our method on large complex meshes, which show results which mostly adjust to B-Rep FACE partition. Within the mutated vector, discontinuities larger than a threshold (interactively set by a human) determine the partition of the original mesh. We then produce a monotonically increasing permutation of the Fiedler vector (2nd eigenvector of Graph Laplacian) for encoding the connectivity among part feature sub-meshes. ![]() We pre-process the mesh to obtain a edge-length homogeneous triangle set and its Graph Laplacian is calculated. Although mesh segmentation is dictated by geometry and topology, this article focuses on the topological aspect (graph spectrum), as we consider that this tool has not been fully exploited. In design and manufacturing, mesh segmentation is required for FACE construction in boundary representation (B-Rep), which in turn is central for feature-based design, machining, parametric CAD and reverse engineering, among others. ![]() It can effectively divide the point set into several groups to achieve the model segmentation. ![]() The experimental results demonstrate that (1) the proposed approach can effectively transform the b-rep model into a two-dimensional coordinate point set (2) the k -means algorithm can efficiently cluster points to achieve segmentation and (3) in view of human cognition, the segmentation results are more reasonable. The k -means approach with the Silhouette coefficient was employed to conduct unsupervised learning of the coordinate points. By means of PERT, spectral theory, and the CAD models’ geometrical and topological information, we transform the b-rep model faces into two-dimensional coordinate points corresponding to the nodes of the attributed adjacent graph (AAG). In this article, we first propose a novel CAD model segmentation method that uses the fusion of the program/project evaluation and review technique (PERT) and the Laplacian spectrum theory. įor complex CAD models, model segmentation technology is an important support for model retrieval and reuse. For larger mesh models the overall preprocessing time is still only a matter of seconds, with file read time being a significant. In general, mesh models with fewer than 1,000,000 vertices require 1 second or less additional time to create the hierarchy and normals. Additional time is also required to preprocess the hierarchy, but it is very short because the representative surface normals for the hi- erarchy levels are quickly calculated from given normals or from easily interpolated normals. A coarse-to-fine selection using an octree hierarchy greatly reduced the com- putation time required to partition larger models, but due to the characteristic of all hierarchical approaches to sometimes overcommit with insufficient data, more user interaction is sometimes required. The hierarchical method cuts the processing time in half with nearly identical results. ![]() Another example can be seen for the larger gargoyle model in Figure 2.13. example of partitioning using hierarchical acceleration can be seen in Figure 2.12, in which a model with more than a half-million vertices was interactively segmented in approximately one minute.
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