CAREER: Geometrically Coherent Image Interpretation

职业：几何相干图像解释

• 批准号: 0546547
• 负责人: Alexei Efros
• 金额: $ 49.95万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-02-01 至 2012-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0546547&HistoricalAwards=false
• 关键词: CAREER; Geometrically; Coherent; Image; Interpretation

CAREER: Geometrically Coherent Image InterpretationPI: Alexei A. EfrosAbstractImage interpretation, the ability to see and understand the three-dimensional world behind a two-dimensional image, goes to the very heart of the computer vision problem. The overall objective of this proposal is, given a single image, to automatically produce a coherent interpretation of the depicted scene. On one level, suchinterpretation should include opportunistically recognizing known objects (e.g. people, houses, cars, trees) and known materials (e.g. grass, sand, rock, foliage) as well as their rough positions and orientations within the scene. But more than that, the goal is to capture the overall "sense of the scene" even if we do not recognize some of its constituent parts.To address this extremely difficult task, the PI proposes a novel framework that aims to jointly model the elements that make up a scene within the geometric context of the 3D space that they occupy. Because none of the measured quantities in the image -- geometry, materials, objects and object parts, scene classes, camera pose, etc. -- are reliable in isolation, they must all be considered together, in a coherent way. Having the geometric context representation will allow all the elements of the image to be physically "placed" within this contextual frame and will permit reasoning between them and their 3D environment in a joint optimization framework. During the timeframe of this proposal, the PI will develop such a framework which will allow a geometrically coherent semantic interpretation of a image to emerge.Intellectual Merit: At the core of the proposal is an effort to unify two disjoint computer vision philosophies -- the traditional "Geometry" school that deals with 3D quantities like points and surfaces, and the newer "Appearance" school that operates in terms of 2D pixel patterns. These two views are here combined into one coherent framework, where appearance and geometry co-exist and rely on each other to jointly produce an interpretation of an image.Broader Impact: There are a number of important real-world problems that will benefit from the proposed research even during its development. Direct applications of this work include: developing navigation assistant technology for the visually impaired, scene awareness for mobile robots and car safety, and creating graphical 3D walk-through environments from a single image. URL: http://www.cs.cmu.edu/~efros/ImageInterpretation/

职业：几何相干图像解释：Alexei A. efrosabstractimage解释，能够看到和理解二维图像背后的三维世界的能力，是计算机视觉问题的核心。 该提案的总体目标是给出一个图像，可以自动对所描绘的场景产生连贯的解释。 在一个层面上，这种解释应包括机会主义地识别已知物体（例如人，房屋，汽车，树木）和已知材料（例如草，沙子，岩石，叶子）以及现场的粗糙位置和方向。 但不仅如此，即使我们不认识到它的某些组成部分也是要捕获整体“场景意识”。要解决这一极为艰巨的任务，PI提出了一个新颖的框架，旨在共同建模构成他们所占据的3D空间几何场景中场景的元素。 由于图像中没有测量的数量 - 几何形状，材料，对象和对象零件，场景类，相机姿势等 - 孤立地可靠，因此必须以连贯的方式一起考虑它们。 具有几何上下文表示将允许图像的所有元素在此上下文框架内物理地“放置”，并将允许在关节优化框架中它们与其3D环境之间的推理。 During the timeframe of this proposal, the PI will develop such a framework which will allow a geometrically coherent semantic interpretation of a image to emerge.Intellectual Merit: At the core of the proposal is an effort to unify two disjoint computer vision philosophies -- the traditional "Geometry" school that deals with 3D quantities like points and surfaces, and the newer "Appearance" school that operates in terms of 2D pixel patterns. 这两种观点在这里结合在一起，在一个连贯的框架中，外观和几何形状共存并互相依靠以共同产生图像的解释。Broader的影响：即使在开发过程中，也有许多重要的现实世界问题，这些问题也将从拟议的研究中受益。 这项工作的直接应用包括：为视力障碍开发导航助理技术，移动机器人和汽车安全的场景意识，以及从单个图像创建图形3D步行环境。 URL：http：//www.cs.cmu.edu/~efros/imageinterpretation/