RI: Small: Exploiting Geometric and Illumination Context in Indoor Scenes

RI：小：利用室内场景中的几何和照明环境

• 批准号: 0916014
• 负责人: David Forsyth
• 金额: $ 45万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0916014&HistoricalAwards=false
• 关键词: RI; Small; Exploiting; Geometric; Illumination

The research objective is to investigate methods to recover geometry and perform spatial reasoning in rooms. This project aims to recover the room space, illumination, and object layout from an image. Together, these elements capture the layout of the room walls, the location of objects in the image and the 3D space, and a lighting representation that allows illumination artifacts to be explained and rooms to be relit with inserted objects. The work takes an integrated approach, exploiting constraints within and between spatial representations. The project also aims to leverage knowledge of room geometry to better reason about surface utility, enabling advanced spatial analysis of indoor scenes. This research unifies ideas from geometry, multiple view computer vision, shading, and statistics to recover complex spatial representations from single views. The work further aims to create tools for object insertion and removal and scene completion, allowing the average person to more easily create the photograph that she wants or an interior designer to quickly sketch a photorealistic prototype of a new concept. The recovered spatial information also enables mobile robots to find walkable paths through cluttered rooms and to understand how objects can be physically manipulated and placed, which is essential for assistive household robotics. Other anticipated applications include surveillance, security, and transportation safety. The project contributes to education through student projects, course development, and workshops and tutorials involving a broader audience.

研究目标是研究恢复几何形状并在房间中执行空间推理的方法。 该项目旨在从图像中恢复房间空间，照明和对象布局。 这些元素一起捕获了房间墙的布局，图像和3D空间中的对象的位置以及允许解释照明伪像的照明表示，并用插入的对象保留房间。 这项工作采用综合方法，利用空间表示内部和之间的约束。 该项目还旨在利用房间几何形状的知识，以更好地了解表面效用，从而实现对室内场景的高级空间分析。 这项研究统一了从几何形状，多视图计算机视觉，阴影和统计数据中统一的想法，以从单一视图中恢复复杂的空间表示。 这项工作进一步旨在为对象插入，拆卸和场景的完成创建工具，使普通人更容易地创建她想要的照片或室内设计师快速绘制新概念的逼真的逼真的原型。 恢复的空间信息还使移动机器人能够在混乱的房间中找到可步行的路径，并了解如何对物体进行物理操纵和放置，这对于辅助家用机器人技术至关重要。 其他预期的申请包括监视，安全和运输安全。 该项目通过学生项目，课程发展以及讲习班以及涉及更广泛受众的教程为教育做出了贡献。