RI: Medium: Collaborative Research: Physically Grounded Object Recognition

提案标题：国际扶轮：中等：协作研究：物理基础目标识别机构：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(公共法律111-5)资助的。虽然世界是非常三维的，但当今的大多数视觉目标识别方法基本上将问题简化为2D模式分类，其中矩形图像块被独立地与商店模板进行比较，以在图像中产生孤立的目标标签。这个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来探索定性几何推理，从而解释现实世界的三维本质。该项目围绕两个主要研究领域展开。定性3D场景分析：我们工作的核心部分将是开发描述所描述的对象和表面及其物理关系的场景的定性3D模型。场景中的地物：我们将场景的几何表示和对应的三维空间关系与目标识别过程相结合，方法是：(1)根据场景组件之间的三维关系推断出一组可能的对象标识：(2)从场景布局中预测最可能的对象位置；和(3)使用遮挡关系和深度排序来预测可能在场景中可见的对象的部分。该项目预计将导致从照片理解3D场景的重大进展，这是一项关键的使能技术，用于广泛的应用，包括自主系统、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、监视和安全以及运输。国家科学基础建议摘要：0905402 PI姓名：赫伯特，军事打印自eJacket：05/06/09第1页，共1页

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