Exploratory Research in Scene Analysis and Object Recognition

场景分析与物体识别的探索性研究

• 批准号: 0745636
• 负责人: Martial Hebert
• 金额: --
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2009-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0745636&HistoricalAwards=false
• 关键词: Exploratory; Research; Scene; Analysis; Object

AbstractIn this SGER proposal, the PIs propose to develop novel tools that allow qualitative 3D vision from 2D images and video sequences. Most of today's approaches to visual object recognition essentially reduce this problem to one of pattern classification, where rectangular image patches are independently compared to stored templates to produce isolated object labels. The proposed research explores new research directions for the task of recovering the 3D layout of a scene from a single image and for using the 3D layout to help in recognizing object categories in a scene. Each of the research directions proposed for exploration has the potential of opening up an entire new set of approaches and algorithms and has the potential of defining an entire new field of Computer Vision, which the PIs call "qualitative geometric reasoning", as opposed to the traditional quantitative approaches which assume precise depth and dense measurements from stereo or SFM. By advocating the use of qualitative geometric reasoning, this body of work is expected to contribute to a radical change in the way the image interpretation and scene analysis problems are tackled in the computer vision community.The proposed research is anticipated to result in new directions in the general area of geometric reasoning for scene analysis, which is a critical enabling technology for a wide range of applications including defense, health care, human-computer interaction, image retrieval and data mining, industrial and personal robotics, manufacturing, scientific image analysis, space exploration, surveillance and security, and transportation.

AbstractIn this SGER proposal，PI建议开发新的工具，允许从2D图像和视频序列的定性3D视觉。今天的大多数视觉对象识别的方法基本上减少了这个问题的模式分类，其中矩形图像补丁独立地比较存储的模板，以产生孤立的对象标签。拟议的研究探索新的研究方向的任务，从一个单一的图像恢复的三维布局的场景，并使用三维布局，以帮助识别对象类别的场景。每一个研究方向都有可能开辟一套全新的方法和算法，并有可能定义一个全新的计算机视觉领域，PI称之为“定性几何推理”，而不是传统的定量方法，这些方法假设立体或SFM的精确深度和密集测量。通过倡导使用定性几何推理，这一工作机构预计将有助于从根本上改变图像解释和场景分析问题在计算机视觉社区的处理方式。拟议的研究预计将导致新的方向，在一般领域的几何推理场景分析，这是一个关键的使能技术，为广泛的应用，包括国防，医疗保健、人机交互、图像检索和数据挖掘、工业和个人机器人、制造业、科学图像分析、空间探索、监控和安全以及运输。