By Charlie C. L. Wang
The fresh development in user-customized product layout calls for the form of goods to be immediately adjusted in accordance with the human body’s form, in order that humans will consider more well-off whilst donning those items. Geometric techniques can be utilized to layout the freeform form of goods worn via humans, which could significantly increase the potency of layout methods in numerous industries related to personalized items (e.g., garment layout, toy layout, jewel layout, shoe layout, and layout of clinical units, etc.). those items are typically composed of very complicated geometric shapes (represented through free-form surfaces), and aren't pushed through a parameter desk yet a electronic human version with free-form shapes or a part of human our bodies (e.g., wrist, foot, and head models).
Geometric Modeling and Reasoning of Human-Centered Freeform items introduces the algorithms of human physique reconstruction, freeform product modeling, constraining and reconstructing freeform items, and form optimization for making improvements to the manufacturability of freeform items. in keeping with those ideas, the layout automation challenge for human-centered freeform items could be essentially solved.
Researchers and builders engaged on difficulties of automated designing separately personalized items can use this publication as a reference, and it might probably even be utilized in classes in computer-aided product layout on the graduate level.
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Additional info for Geometric Modeling and Reasoning of Human-Centered Freeform Products
30) with nti being the unit normal vector on the template model MT . A very small number should be selected for the offset value ω. As suggested by Li et al. 5 cm is employed for the scanned human models. 3 Pose Alignment Given the sample points ti∗ ∈ φ ∗ ( M˜ T∗ ) with sign-flip corrected, the approximatenearest-neighbor (ANN) search  is employed to find the closest points c∗ (ti∗ ) ∈ ∗ of t ∗ . Using these correspondences, the mapping of samples in 3 from M M˜ H T i to M H is defined as ti → c(ti ) ∈ M H .
The computation can be completed in one minute on a PC with moderate configuration. Another interesting study is about the number of sample points used in the pose alignment step and its effect on the final matching result. According to the experimental tests reported in , the pose alignment results do not lead to a satisfactory matching result if a small number of sample points are used. However, it does not mean that the more sample points are used, the more accurate result can be obtained.
17), if a turning point (which is marked as p3 in Fig. 17) is found, it is the belly-button point. 1 On a 2D polygon, if the positions of three adjacent points pi−1 , pi , and pi+1 make the value of angle ∠pi−1 pi pi+1 smaller than a threshold, pi is considered as a turning point. 2 Feature Point Extraction 33 Fig. 17 A rule-based method to determine key feature points on a human model Busty Points. From the turning point p4 on the silhouette of the right view, the height of busty points, h busty , can be obtained.