面向理解的室内点云场景空间结构恢复与表达

项目名称： 面向理解的室内点云场景空间结构恢复与表达

项目编号： No.61472319

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： 王映辉

作者单位： 西安理工大学

项目金额： 80万元

中文摘要： 对场景进行感知与理解是计算机视觉领域的重要研究课题。本项目选择室内点云场景为研究对象:(1)在基于横向切割所得的二维曲线的基础上，分析这些二维曲线的几何特征、拓扑特征以及它们之间的空间关联特征，进而探索新的室内场景基本形状曲面的提取方法，期盼解决室内场景基本形状的分解问题；(2)探讨基于BlobTree的室内场景基本形状曲面和物体的空间排列关系和关联关系，获得室内场景的空间分布模型体系，期盼解决室内场景及其所含物体的结构表达和提取问题，并为模式库的构建提供理论支撑。(3)在场景的空间分布模型体系的基础上，探索空间复杂数据库的构建模式，进而搭建在此模式支撑下的、基于基本形状曲面的空间复杂数据库，期盼解决室内场景认知和理解中的匹配问题。该项目的研究成果为实现高级场景理解中的对象识别和和整体布局理解、及空间三维关系的推理奠定基础，并为一般点云场景的认知提供新的思路。

中文关键词： 室内场景；横向切割；形状组合；曲线分析；场景理解

英文摘要： Scene perception and understanding is an important research topic in computer vision. Our research focuses on the indoor point clouds: (1) After slicing the indoor point clouds horizontally, we can obtain the two-dimensional curves whose geometric feature, topological feature and spatial association can then be analyzed. Then we explore a new shape extraction method aiming at decomposing the indoor scenes into the basic shapes. (2) Analyzing the spatial arrangement and association of the basic shapes and objects based on BlobTree in order to get a systematic spatial distribution model of the indoor scenes. We aim at solving the problem of structure expression and objects extraction for indoor scene, and providing theoretical support for the 3D model library building. (3) Exploring the constructive mode of the space complexity database and building the database based on the basic shapes, we mean to solve the matching problem in scene understanding and perception. This research lays the foundation for the high-level 3D object recognition, overall layout understanding and spatial reasoning of the scene understanding. At the same time, it provides new ideas for the other point cloud scene cognition.

英文关键词： scanned indoor scene;horizontal slicing;shape assemble;curve analysis;scene perception