By Charlie C. L. Wang
The fresh development in user-customized product layout calls for the form of goods to be instantly adjusted in line with the human body’s form, in order that humans will believe more well-off while donning those items. Geometric ways can be utilized to layout the freeform form of goods worn through humans, that can significantly increase the potency of layout tactics in quite a few industries concerning custom-made items (e.g., garment layout, toy layout, jewel layout, shoe layout, and layout of scientific units, etc.). those items are typically composed of very advanced geometric shapes (represented by means of free-form surfaces), and aren't pushed by means of 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 line with those recommendations, the layout automation challenge for human-centered freeform items should be essentially solved.
Researchers and builders engaged on difficulties of computerized designing separately personalized items can use this booklet as a reference, and it may even be utilized in classes in computer-aided product layout on the graduate level.
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Additional resources for Geometric Modeling and Reasoning of Human-Centered Freeform Products
In this approach, the patch parameterization based on mean-value coordinates is employed to establish the bijective mapping between patches. It can be applied to the 3D-to-2D mapping as well as the 2D-to-2D mapping if one of the 2D patch is considered as a 3D patch to compute the mean-value coordinates. By the mapping in Eq. 35), the mesh connectivity on the template human body T can be transformed to any other individuals H to obtain the mesh surfaces with consistent connectivity. Then, shape blending can be easily conducted by blending the positions of the corresponding vertices (see Fig.
Second, the surface fitting step refines the surface of the transformed template by optimizing the fitness and the smoothness iteratively. Two main processes, surface fitness optimization and surface smoothing, are repeatedly applied until changes on the surface converge to a limited amount. The surface fitting procedure employs a bidirectional mapping concept and an orientation-aware movement to improve the fitting quality of the template model. • Third, the feature matching refinement step further refines the correspondences by adopting feature descriptor constraints on particular surface regions.
48], the quality of processed point sets by using different values for 21 L kavg does not have significant differences. The value of 21 L kavg mainly affects the speed of computation. 30 2 Digital Human Body Fig. 15 Progressive results show how the points are filled into the missed regions by ICO (top row). 5 Discussion For some point data which are embedded with small holes only, reconstruction algorithms (such as RBF and POS) can successfully generate a surface without being affected by the holes.
Geometric Modeling and Reasoning of Human-Centered Freeform Products by Charlie C. L. Wang