The Role Learning in Perceptual Organization of Complex Images

复杂图像感知组织中的角色学习

• 批准号: 9907141
• 负责人: Sudeep Sarkar
• 金额: $ 22.57万
• 依托单位: University of South Florida
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-08-15 至 2003-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9907141&HistoricalAwards=false
• 关键词: Role; Learning; Perceptual; Organization; Complex

Abstract IIS-9907141Sarkar, SudeepUniversity of South Florida$73,407 - 12 mos.The Role of Learning in Perceptual Organization of Complex ImagesThis is the first year funding of a three year continuing award. Perceptual organization is the ability to efficiently group low-levelprimitives, such as pixels or edge segments or regions, so as to formobject hypotheses with minimal domain knowledge. This process is anessential link between the noisy low-level segmentation processes andthe sophisticated, computationally expensive, object recognitionprocesses. This work will address three major scientific issuesrelated to perceptual organization in computer vision: (i) How toefficiently form large groups of extended low-level primitives byassembling small groups of features (grouplets)? The concept of graphspectra is an ideal mechanism for this purpose. (ii) How to encodethe dependency of grouping parameters on image statistics? Jointprobability distributions encoded as Bayesian networks offer anefficient abstraction. (iii) What is the role of learning inperceptual organization? The specific roles of learning explored wouldbe threefold: (a) learning the image to grouping parameter mapping,(b) learning the forms of the groups, and the associated hierarchy,from object models, and (c) learning the primitive type, such ascorners, textured-regions, or edges, that is appropriate for a domain.

摘要IIS-9907141 Sarkar，南佛罗里达大学苏迪普73,407 - 12月。学习在复杂图像感知组织中的作用这是一个为期三年的连续奖项的第一年资助。感知组织是一种有效地将低层次的基元（如像素或边缘片段或区域）进行分组的能力，以便用最少的领域知识形成对象假设。这个过程是噪声低级别分割过程和复杂的，计算昂贵的对象分割过程之间的重要联系。这项工作将解决与计算机视觉中的感知组织相关的三个主要科学问题：（i）如何通过组装小组特征（小组）有效地形成大组的扩展低级原语？图谱的概念是实现这一目的的理想机制。 (ii)如何编码分组参数对图像统计的依赖性？ 联合概率分布编码为贝叶斯网络提供了一个有效的抽象。(iii)学习无知觉组织的作用是什么？探讨学习的具体作用有三个方面：（a）学习图像到分组参数映射，（B）从对象模型学习组的形式和相关的层次结构，以及（c）学习适合于域的基本类型，如角、纹理区域或边缘。