Notice
This item was automatically migrated from a legacy system. It's data has not been checked and might not meet the quality criteria of the present system.
Leimer, K., Gersthofer, L., Wimmer, M., & Musialski, P. (2017). Relation-Based Parametrization and Exploration of Shape Collections. Computers and Graphics, 67, 127–137. https://doi.org/10.1016/j.cag.2017.07.001
Human-Computer Interaction; General Engineering; Computer Graphics and Computer-Aided Design; 3d database exploration; Model variability; Shape analysis; Shape collections
-
Abstract:
With online repositories for 3D models like 3D Warehouse becoming more prevalent and growing ever larger, new possibilities have emerged for both experienced and inexperienced users. These large collections of shapes can provide inspiration for designers or make it possible to synthesize new shapes by combining different parts from already existing shapes, which can be both easy to learn and a fas...
With online repositories for 3D models like 3D Warehouse becoming more prevalent and growing ever larger, new possibilities have emerged for both experienced and inexperienced users. These large collections of shapes can provide inspiration for designers or make it possible to synthesize new shapes by combining different parts from already existing shapes, which can be both easy to learn and a fast way of creating new shapes. But exploring large shape collections or searching for particular kinds of shapes can be difficult and time-consuming tasks as well, especially considering that online repositories are often disorganized. In our work, we propose a relation-based way to parametrize shape collections, allowing the user to explore the entire set of shapes based on the variability of spatial arrangements between pairs of parts. The way in which shapes differ from each other is captured automatically, resulting in a small number of exploration parameters. Furthermore, a copy-and-paste system for parts allows the user to change the structure of a shape, making it possible to explore the entire collection from any initial shape.
en
Research Areas:
Visual Computing and Human-Centered Technology: 100%