课题基金 / 基金详情

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

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:
$45.0万
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
项目状态:
已结题
起止时间:
2009-09-01 至 2013-08-31

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中文摘要
翻译
研究目的是探讨在房间中恢复几何形状和进行空间推理的方法。该项目旨在从图像中恢复房间空间,照明和物体布局。这些元素共同捕捉了房间墙壁的布局,图像和3D空间中物体的位置,以及允许解释照明人工制品的照明表现,并通过插入的物体再现房间。这项工作采用了一种综合的方法,利用空间表征内部和之间的约束。该项目还旨在利用房间几何知识来更好地解释表面效用,从而实现室内场景的高级空间分析。本研究将几何学、多视图计算机视觉、阴影和统计学的思想结合起来,从单个视图中恢复复杂的空间表示。这项工作进一步旨在创建对象插入和移除和场景完成的工具,使普通人更容易创建她想要的照片,或室内设计师快速勾勒出新概念的逼真原型。恢复的空间信息还使移动机器人能够在杂乱的房间中找到可行走的路径,并了解如何对物体进行物理操作和放置,这对辅助家用机器人至关重要。其他预期的应用包括监视、安保和运输安全。该项目通过学生项目、课程开发以及涉及更广泛受众的研讨会和教程来促进教育。
英文摘要
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.
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会议论文
RI: Medium: Creating Knowledge with All-Novel-Class Computer Vision
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INT2-Medium: Understanding the meaning of images
Interpreting Human Behaviour in Video using FSA's and Object Context
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