Simplification algorithm of 3D model is basic, important technology that can reduce the redundancy of the expanding 3D shape data, and that can apply to various applications. The QEM method is given as an algorithm to simplify data while preserving the feature of 3D model. The QEM method is one of the algorithms with the best balance between details and the simplification speed after the vertex is degenerated. However, because the QEM method is a successive algorithm that can delete only one edge at a time, it takes time for simplification of the huge 3D models. PC cluster is one of the environment that can enlarge computational resources with uniting many PCs. It is constructed easily and used generally. In this paper, it proposes the method made parallel by extending the QEM method, and using the PC cluster. With the PC cluster constructed by typical windows PCs, simplification high-speed by this method becomes possible while maintaining the feature of 3D model.
For point cloud data obtained from 3D scanning devices, excessively large storage and long postprocessing time are required. Due to this, it is very important to simplify the point cloud to reduce calculation cost. In this paper, we propose a new point cloud simplification method that can maintain the characteristics of surface shape for unstructured point clouds. In our method, a segmentation range based on mean curvature of point cloud can be controlled. The simplification process is completed by maintaining the position of the representative point and removing the represented points using the range. Our method can simplify results with highly simplified rate with preserving the form feature. Applying the proposed method to 3D stone tool models, the method is evaluated precisely and effectively.
The appearance of a product has led to a trend for a consumer to purchase a product. Some products have shapes or parts that don't fulfill the consumer's desires and needs. This mean that often, choice of a consumer is inspired by the shape of a product. Therefore, It might be interesting to study on perception of shape in terms of semantic associations. The aim of this study is to investigate people's perception on gender of 3D-shape in terms of semantic association such as "feminine" or "masculine". In this paper we observed the effect of variable base on perceiving gender kansei of 3D-shapes. To assess base-variance of 3D-shape, we examined whether convexity and concavity of base in the context of sharp and curved forms. Results of our psychophysical experiment will be very important and helpful in the kansei-driven design.
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