High-level Shape Representations for Content Creation

我们建议调查高级表示法，以促进内容创建。几何内容的创建是计算机图形和动画、视觉效果、游戏开发和面向制造的设计等领域的一项重要任务。创建3D内容的最常见方法是直接对3D形状的几何图形进行建模。然而，建模是一项费力的任务，其中艺术家需要熟练地使用传统的软件工具，这些工具通常涉及低级形状表示，例如三角形网格。 因此，在过去的十年里，计算机图形学的努力集中在促进3D模型创建的任务上。这一方向的最新趋势是将形状表示为在更多语义级定义的基元的集合，例如形状部分(如椅子的腿、座位和靠背)。这些表示允许在更抽象的级别上操作形状，而不依赖于底层的低级别表示。高级表示还可用于合成新模型，或通过捕获形状的结构和外观的其他方面来指导形状的建模或探索形状空间。 在这种情况下，建议的研究计划的目标是开发用于形状处理和合成的高级表示，以促进几何内容的创建，特别是3D形状。这种表示的成功使用需要三个组件：1)适合于目标应用的形状表示；2)自动或半自动地构建用于现有几何数据的表示的算法；以及3)允许用户使用表示用于内容创建的指导机制。因此，这三个组成部分构成了该计划的研究流。 在第一个流程中，我们将研究更适合于操作和合成的形状表示的设计。在第二个流程中，我们的目标是研究大数据分析如何能够导致形状分析的重大进步，并促进高级表示的自动构建。在第三个流程中，我们将研究支持创造性建模的指导机制的发展。我们预计，从长远来看，该计划将有助于促进内容的创作，从而引起设计和娱乐行业的兴趣。

We propose to investigate high-level representations to facilitate content creation. The creation of geometric content is an important task in areas such as computer graphics and animation, visual effects, game development, and fabrication-oriented design. The most common approach for creating 3D content is by directly modeling the geometry of 3D shapes. However, modeling is a laborious task where artists need to be skilled to use the conventional software tools, which typically involve working on low-level shape representations, e.g., triangle meshes. Thus, during the last decade, efforts in computer graphics have focused on the task of facilitating the creation of 3D models. A recent trend towards this direction is to represent shapes as a collection of primitives defined at a more semantic level, e.g., shape parts (such as the legs, seat and back of a chair). These representations allow manipulating shapes at a more abstract level, independently of the underlying low-level representation. High-level representations can also be used to synthesize new models or to guide the modeling of shapes or exploration of a shape space by capturing additional aspects of the structure and appearance of shapes. In this context, the goal of the proposed research program is to develop high-level representations for shape manipulation and synthesis to facilitate the creation of geometric content, especially 3D shapes. The successful use of such representations requires three components: 1) A shape representation that is suitable for the target applications; 2) Algorithms that automatically or semi-automatically build the representations for existing geometric data; and 3) Guiding mechanisms that allow a user to employ the representations for content creation. Thus, these three components comprise the research streams of the program. In the first stream, we will investigate the design of shape representations that are more suitable for manipulation and synthesis. In the second stream, our goal is to study how big data analytics can lead to significant advancements in shape analysis, and facilitate the automatic construction of the high-level representations. In the third stream, we will investigate the development of guiding mechanisms that can support creative modeling. We expect that, in the long term, this program can contribute to facilitating the creation of content and thus be of interest to the design and entertainment industries.