RI: Small: Visual Parts for Image and Video Analysis

RI：小型：用于图像和视频分析的视觉部件

• 批准号: 0915924
• 负责人: Carlo Tomasi
• 金额: $ 10万
• 依托单位: Duke University
• 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: 2009-09-15 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0915924&HistoricalAwards=false
• 关键词: RI; Small; Visual; Parts; Image

Images and video are analyzed in terms of parts. Qualitatively,a part of an image is a region that can be extracted consistently, even if the image changes somewhat because of differences in quality, resolution, lighting, viewpoint, or small variations in the shape of the objects being depicted. In video, these regions are extruded into time, forming tubes of sorts that persist over relatively long time intervals.Technically, parts are regions with high saliency and stability, two notions that are defined anew in this research based on mathematical tools that span from harmonic functions to new developments in computational topology and spectral graph theory.Parts are a key handle into image and video structure, as they allow describing the visual information succinctly and in a stable manner. They lead to indices for retrieval, and provide primitives that make it possible for computer software to recognize objects and activities. The main result from this effort is a systematic comparison of advantages and limitations of the new definition with descriptors from the literature.Applications of part-based visual analysis range from image retrieval, medical and biological imaging, and video interpretation for military and intelligence scenarios, to surveillance, the annotation and editing of images and video clips, and more. Work involves graduate students and undergraduates funded through the NSF REU program. Results of this research are disseminated through scholarly publications and classes at Duke University. A benchmark of evaluation images and video is developed for open use by the research community.

图像和视频按部分进行分析。质量上，图像的一部分是可以一致地提取的区域，即使图像由于质量，分辨率，照明，视点或所描绘对象形状的微小变化而有所变化。在视频中，这些区域被挤压到时间中，形成各种各样的管道，持续相对较长的时间间隔。从技术上讲，部分是具有高显着性和稳定性的区域，这两个概念在本研究中基于数学工具重新定义，这些工具涵盖从调和函数到计算拓扑和谱图理论的新发展。部分是图像和视频结构的关键处理，因为它们允许以简洁和稳定的方式描述视觉信息。它们导致检索索引，并提供原语，使计算机软件能够识别对象和活动。这项工作的主要结果是一个系统的比较的优点和限制的新定义与描述符从literature.Applications的基于部分的视觉分析范围从图像检索，医学和生物成像，视频解释军事和情报场景，监视，注释和编辑的图像和视频剪辑，等等。工作涉及通过NSF REU计划资助的研究生和本科生。这项研究的结果通过学术出版物和杜克大学的课程传播。一个基准的评估图像和视频开发的研究界开放使用。