数据驱动的室内场景设计与建模

项目名称： 数据驱动的室内场景设计与建模

项目编号： No.61472377

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 计算机科学学科

项目作者： 陈雪锦

作者单位： 中国科学技术大学

项目金额： 80万元

中文摘要： 室内场景的计算机辅助设计广泛应用于建筑、家居设计、家具制造等行业。低价深度相机的发展和网络三维模型资源的丰富，为室内场景设计技术带来了新的契机。数据驱动的室内场景设计是近年来的一个研究热点。然而，现有的室内场景相关技术都局限在特定的建模问题，不适于室内设计。其根本原因在于室内设计过程包含了众多艺术性的、不同内容的一系列设计原则，尚无一种适用于设计过程的通用表达。本课题尝试从一个完整的室内设计角度，研究一种包含室内场景几何、布局、外观的室内设计的通用表达方法。充分挖掘大数据中所蕴含的潜在信息，确定室内设计通用表达的量化模型。主要研究内容包括：研究室内设计原则的表达，研究在大数据中总体设计模型的高效学习算法，研究在不同条件下的自适应场景设计算法。本课题预期完成一个有效的交互室内设计系统，在室内场景计算机辅助设计方法的理论上有所突破，在室内场景建模技术上有所创新，为其理论化和实用化奠定基础。

中文关键词： 计算机辅助设计；室内场景；三维建模；外观设计；因子图

英文摘要： Computer-Aided interior design is widely used in architecture, home design, furniture manufacture and so on. The development of low-cost depth cameras and 3D models on the Internet brings a novel opportunity for computer-aided interior design. Data-driven interior scene design has becomes one of the hottest research topics in computer graphics recently. However，existing techniques for interior design are limited to some specific modeling problems, which makes it far from the requirements of the interior design. The fundamental reason is that there is not a general formulation suitable for interior design which consists of a number of abstract artistic principles for different contents. We are going to present a novel general formulation of the interior design problem, combining geometry, arrangements, and appearance of the indoor scene. In order to determine its quantitative expression，mining it from a large dataset of indoor scene models is to be studied. The main research contents include: study of the key principles of interior design and their mathematical descriptions; learning the quantitative model effectively from a big dataset of indoor scenes; study of the 3D modeling and design algorithms under different constraints specified by common users. This project is expected to present an effective system for interior design, to achieve theory breakthrough and innovations of interior design and modeling techniques.

英文关键词： Computer Aided Design;Indoor Scenes;3D Modeling;Appearance Design;Factor Graph