RI: Medium: Collaborative Research: Physically Grounded Object Recognition

RI：媒介：协作研究：物理接地物体识别

• 批准号: 0904209
• 负责人: Derek Hoiem
• 金额: $ 41.6万
• 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: 2009-07-01 至 2013-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0904209&HistoricalAwards=false
• 关键词: RI; Medium; Collaborative; Research; Physically

Proposal Title: RI: Medium: Collaborative Research: Physically Grounded ObjectRecognitionInstitution: Carnegie-Mellon UniversityAbstract Date: 05/05/09"This award is funded under the American Recovery and Reinvestment Act of 2009(Public Law 111-5)."Although the world is very much three-dimensional, most of today's approaches tovisual object recognition essentially reduce the problem to one of 2D patternclassification, where rectangular image patches are independently compared to storedtemplates to produce isolated object labels within the image. This project aims toaccount for the three-dimensional nature of the real world by exploring qualitativegeometric reasoning in terms of 3D spatial relationships between scene components,category-level object models, and global scene understanding.The project is organized around two major research areas. Qualitative 3D sceneparsing: A central part of our effort will be to develop qualitative 3D models of the scenethat describe the depicted objects and surfaces and their physical relations. Groundingobjects in the scene: We integrate the geometric representation of the scene and thecorresponding 3D spatial relations with the object recognition process by (1) inferringthe set of likely object identities based on 3D relations among scene components; (2)predicting the most likely object locations from the scene layout; and (3) using theocclusion relations and depth ordering to predict the parts of objects that may be visiblein the scene.The project is anticipated to result in major advances in 3D scene understanding fromphotographs, a critical enabling technology for a wide range of applications includingautonomous systems, health care, human-computer interaction, assistive technology,image retrieval, industrial and personal robotics, manufacturing, scientific imageanalysis, surveillance and security, and transportation.NATIONAL SCIENCE FOUNDATIONProposal AbstractProposal:0905402 PI Name:Hebert, MartialPrinted from eJacket: 05/06/09 Page 1 of 1

提案标题：RI：媒介：协作研究：物理接地对象识别机构：卡内基梅隆大学摘要日期：05/05/09“该奖项是根据 2009 年美国复苏和再投资法案（公法 111-5）资助的。”尽管世界在很大程度上是三维的，当今大多数视觉对象识别方法本质上将问题简化为二维之一模式分类，其中矩形图像块与存储的模板独立进行比较，以在图像内生成孤立的对象标签。该项目旨在通过探索场景组件之间的 3D 空间关系、类别级对象模型和全局场景理解方面的定性几何推理来解释现实世界的三维性质。该项目围绕两个主要研究领域进行组织。定性 3D 场景解析：我们工作的核心部分是开发场景的定性 3D 模型，描述所描绘的对象和表面及其物理关系。场景中的基础对象：我们通过以下方式将场景的几何表示和相应的 3D 空间关系与对象识别过程集成起来：（1）基于场景组件之间的 3D 关系推断可能的对象身份集； (2)从场景布局中预测最可能的物体位置； (3) 使用遮挡关系和深度排序来预测场景中可能可见的物体部分。该项目预计将在通过照片理解 3D 场景方面取得重大进展，这是一项适用于包括自治系统在内的广泛应用的关键支持技术、医疗保健、人机交互、辅助技术、图像检索、工业和个人机器人、制造、科学图像分析、监视和安全以及交通。国家科学基金会提案摘要提案：0905402 PI 姓名：Hebert, Martial 从 eJacket 打印：05/06/09 第 1 页，共 1 页